MIN Faculty
Department of Informatics
Knowledge Technology

Publications

(Preprints)
 

Kiggundu, A., Weber, C., Wermter, S. A Compressing Auto-encoder as a Developmental Model of Grid Cells. In Abstract Collection of the 1st Human Brain Project (HBP) Student Conference, pp. 35-37, Vienna, Austria, February 2017.

 

Barros, P., Wermter, S. Developing crossmodal expression recognition based on a deep neural model. Adaptive Behavior, 24(5), 373-396, 2016.

 

Heinrich, S., Weber, C., Wermter, S., Xie, R., Lin, Y., Liu, Z. Crossmodal language grounding, learning, and teaching. In Besold, T.R., Bordes, A., Garcez, A.d'A., Wayne, G., editors, Proceedings of the NIPS2016 Workshop on Cognitive Computation (CoCo@NIPS2016), pp. 62-68, Barcelona, ES, December 2016.

 

Cruz, F., Magg, S., Weber, C., and Wermter, S. Training Agents with Interactive Reinforcement Learning and Contextual Affordances. IEEE Transactions on Cognitive and Developmental Systems (TCDS), Vol. 8, Nr. 4, pp. 271-284, doi: 10.1109/TCDS.2016.2543839, December 2016. Open Access.

 

Cruz, F., German I. Parisi, Twiefel, J., and Wermter, S. Multi-modal Integration of Dynamic Audiovisual Patterns for an Interactive Reinforcement Learning Scenario. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.759-766, Daejeon, Korea, 2016.

 

Cruz, F., German I. Parisi, and Wermter, S. Multi-modal Integration of Speech and Gestures for Interactive Robot Scenarios. IEEE/RSJ IROS 2016 Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics, Daejeon, Korea, 2016.

 

Churamani, N., Cruz, F., Griffiths, S., and Barros. P. iCub: Learning Emotion Expressions using Human Reward. IEEE/RSJ IROS 2016 Workshop on Bio-inspired Social Robot Learning in Home Scenarios, Daejeon, Korea, 2016.

 

Wieser, I., Toprak, S., Grenzing, A., Hinz, T., Auddy, S., Karaoğuz, E.C., Chandran, A., Remmels, M., El Shinawi, A., Josifovski, J., Vankadara, L.C., Ul Wahab, F., Bahnemiri, A.M., Sahu, D., Heinrich, S., Navarro-Guerrero, N., Strahl, S., Twiefel, J., Wermter, S. A Robotic Home Assistant with Memory Aid Functionality. Joint German/Austrian Conference on Artificial Intelligence (Künstliche Intelligenz), pp. 102-115, Klagenfurt, Austria, 2016.

 

Hinz, T., Barros, P., and Wermter, S. The Effects of Regularization on Learning Facial Expressions with Convolutional Neural Networks. Proceedings of the 25th International Conference on Artificial Neural Networks (ICANN2016), Part II, LNCS 9887, pp. 80-87, Barcelona, Spain, September 2016.

 

Alpay, T., Heinrich, S., and Wermter, S. Learning Multiple Timescales in Recurrent Neural Networks. Proceedings of the 25th International Conference on Artificial Neural Networks (ICANN2016), Part I, LNCS 9886, pp. 132-139, Barcelona, Spain, 2016.

 

Mici, L., Parisi, G.I., and Wermter, S. Recognition of Transitive Actions with Hierarchical Neural Network Learning. Proceedings of the 25th International Conference on Artificial Neural Networks (ICANN2016), Part II, LNCS 9887, pp. 472-479, Barcelona, Spain, 2016.

 

Twiefel, J., Hinaut, X., Borghetti, M., Strahl, E., Wermter, S. Using Natural Language Feedback in a Neuro-inspired Integrated Multimodal Robotic Architecture. Proceedings of the 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 52-57, New York City, USA, 2016.

 

Parisi, G. I., Magg, S., Wermter, S. Human Motion Assessment in Real Time Using Recurrent Self-Organization. Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 71–76, New York City, USA, 2016.

 

Parisi, G. I.,Wermter, S. Towards Open-Ended Learning of Action Sequences with Hierarchical Predictive Self-Organization. IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), Workshop on Behaviours Adaptation, Interaction and Learning for Assistive Robotics, New York, US, 2016.

 

Wieser, I., Toprak, S., Grenzing, A., Hinz, T., Auddy, S., Karaoğuz, E.C., Chandran, A., Remmels, M., El Shinawi, A., Josifovski, J., Vankadara, L.C., Ul Wahab, F., Bahnemiri, A.M., Sahu, D., Heinrich, S., Navarro-Guerrero, N., Strahl, S., Twiefel, J., Wermter, S. A Robotic Home Assistant with Memory Aid Functionality (video). Proceedings of the 25th IEEE International Symposium on Robot and Human Interactive Communication (RO- MAN), pp. 369, New York City, USA, 2016.

 

Parisi, G. I., Tani, J., Weber, C., Wermter, S. Emergence of multimodal action representations from neural network self-organization. Cognitive Systems Research, in Press, online available since the 22th of August 2016, doi:10.1016/j.cogsys.2016.08.002 , August 2016. Open Access.

 

Barros, P. , Weber, C., Wermter, S. Learning Auditory Representations for Emotion Recognition. Proceedings of International Joint Conference on Neural Networks (IJCNN/WCCI), pp. 921-928, Vancouver, Canada, July 2016.

 

Mousavi, N., Siqueira, H., Barros, P., Fernandes, B., Wermter, S. Understanding How Deep Neural Networks Learn Face Expressions. Proceedings of International Joint Conference on Neural Networks (IJCNN/WCCI), pp. 227-234, Vancouver, Canada, July 2016.

 

Speck, D., Barros, P., Weber, C. and Wermter, S. Ball Localization for Robocup Soccer using Convolutional Neural Networks. RoboCup Symposium, Leipzig, Germany, 2016. - Best Paper Award

 

Cruz, F., Parisi, G. I., and Wermter, S. Learning Contextual Affordances with an Associative Neural Architecture. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pp. 665-670, Bruges, Belgium, 2016.

 

Mici, L., Hinaut, X., and Wermter, S. Activity recognition with echo state networks using 3D body joints and objects category. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pp. 465-470, Bruges, Belgium, 2016.

 

Tsironi, E., Barros, P., and Wermter, S. Gesture Recognition with a Convolutional Long Short-Term Memory Recurrent Neural Network. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pp. 213-218, Bruges, Belgium, 2016.

 

Twiefel, J., Hinaut, X., and Wermter, S. Semantic Role Labelling for Robot Instructions using Echo State Networks. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pp. 695-700, Bruges, Belgium, 2016.

 

Barros, P., Strahl, E., Wermter, S. The iCub Chronicles - Attention to Emotions! , Proceedings of the 10th AAAI Video Competition at the Conference on Artificial Intelligence (AAAI-16) , Phoenix, USA, 2016.

 

Parisi, G.I., Wermter, S. A Neurocognitive Robot Assistant for Robust Event Detection. Trends in Ambient Intelligent Systems: Role of Computational Intelligence, Series "Studies in Computational Intelligence", pp. 1-28, Springer, 2016.

 

Stahlhut, C., Navarro-Guerrero, N., Weber, C., Wermter, S. Interaction in reinforcement learning reduces the need for finely tuned hyperparameters in complex tasks. Kognitive Systeme, 2015-2, doi: 10.17185/duepublico/40718, 2015. Open Access.

 

Hinaut, X., Twiefel, J., Petit, M., Dominey, P., Wermter, S. A Recurrent Neural Network for Multiple Language Acquisition: Starting with English and French, Conference on Neural Information Processing Systems (NIPS 2015), Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches, Montreal, Canada, 2015.

 

Tripathi, N., Oakes, M., Wermter, S. A Scalable Meta-Classifier Combining Search and Classification Techniques for Multi-Level Text Categorization. International Journal of Computational Intelligence and Applications, Volume 14, No. 4, doi:10.1142/S1469026815500200, World Scientific Publishing, 2015.

 

Barros, P., Jirak, D., Weber, C., Wermter, S. Multimodal emotional state recognition using sequence-dependent deep hierarchical features. Neural Networks, Volume 72, Pages 140-151, doi:10.1016/j.neunet.2015.09.009, Elsevier, 2015. Open Access.

 

Parisi, G.I., Weber, C., Wermter, S. Towards Emerging Multimodal Cognitive Representations from Neural Self-Organization. IEEE-RAS International Conference on Humanoid Robots (Humanoids), Workshop on Towards Intelligent Social Robots: Current Advances in Cognitive Robotics, Seoul, South Korea, 2015.

 

Barros, P., Weber, C., Wermter, S. Emotional Expression Recognition with a Cross-Channel Convolutional Neural Network for Human-Robot Interaction. Proceedings of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), Seoul, South Korea, 2015.

 

Barros, P., Wermter, S. Recognizing Complex Mental States with Deep Hierarchical Features for Human-Robot Interaction. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany, 2015.

 

Wermter, S. Neural network models for social robot interaction. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Invited talk at the Workshop on Grounding robot autonomy: Emotional and social interaction in robot behaviour, Hamburg, Germany, 2015.

 

Parisi, G.I., Bauer, J., Strahl, E., and Wermter, S. A Multi-modal Approach for Assistive Humanoid Robots. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Proceedings of the Workshop on Multimodal and Semantics for Robotics Systems (MuSRobS), pp. 10-15, Hamburg, Germany, 2015.

 

Cruz, F., Twiefel, J., and Wermter, S. Performing a Cleaning Task in a Simulated Human-Robot Interaction Environment. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),Workshop An Open-source Recipe for Teaching/Learning Robotics with a Simulator, Hamburg, Germany, 2015.

 

Cruz, F., Parisi, G. I., and Wermter, S. Contextual Affordances for Action-Effect Prediction in a Robotic-Cleaning Task. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),Workshop Learning Object Affordances: A Fundamental Step to Allow Prediction, Planning and Tool Use?, Hamburg, Germany, 2015.

 

Hinaut, X., Twiefel, J., Borghetti Soares, M., Barros, P., Mici, L., Wermter, S. Humanoidly Speaking – How the Nao humanoid robot can learn the name of objects and interact with them through common speech. International Joint Conference on Artificial Intelligence (IJCAI), Video Competition, Buenos Aires, Argentina, 2015.

 

Parisi, G. I.,v. Stosch, F., Magg, S., Wermter, S. Learning Human Motion Feedback with Neural Self-Organization. Proceedings of International Joint Conference on Neural Networks (IJCNN), pp. 2973-2978, Killarney, Ireland, 2015.

 

Hamester, D., Barros, P., Wermter, S. Face Expression Recognition with a 2-Channel Convolutional Neural Network. Proceedings of International Joint Conference on Neural Networks (IJCNN), pp. 1787-1794, Killarney, Ireland, 2015.

 

Cruz, F., Twiefel, J., Magg, S., Weber, C. and Wermter, S. Interactive Reinforcement Learning through Speech Guidance in a Domestic Scenario. Proceedings of International Joint Conference on Neural Networks (IJCNN), pp. 1341–1348, Killarney, Ireland, 2015.

 

Parisi, G. I., Weber, C., Wermter, S. Self-Organizing Neural Integration of Pose-Motion Features for Human Action Recognition. Frontiers in Neurorobotics, Vol. 9, No. 3, 10.3389/fnbot.2015.00003, 2015. Open Access.

 

Stahlhut, C., Navarro-Guerrero, N., Weber, C., and Wermter, S. Interaction Is More Beneficial in Complex Reinforcement Learning Problems than in Simple Ones. Proceedings of the Interdisziplinärer Workshop Kognitive Systeme, pp. 142–150. Bielefeld, Germany, 2015.

 

von Poschinger, D., Weber, C., Wermter, S. A Generative Model of Decorrelating Color Sensitive Retinal Ganglion Cells. Proceedings of the 11th Göttingen Meeting of the German Neuroscience Society, Göttingen, Germany, 2015.

 

Jirak, D., Barros, P.,Wermter, S. Dynamic Gesture Recognition Using Echo State Networks. Proceedings of 23th European Symposium on Artifical Neural Networks, Computational Intelligence and Machine Learning, ESANN'15, pp. 475-480, Bruges, Belgium, 2015.

 

Borghetti Soares, M., Barros, P., Parisi, G. I.,Wermter, S. Learning objects from RGB-D sensors using point cloud-based neural networks. Proceedings of 23th European Symposium on Artifical Neural Networks, Computational Intelligence and Machine Learning, ESANN'15, pp. 439-444, Bruges, Belgium, 2015.

 

Bauer, J., Magg, S., Wermter, S. Attention modeled as information in learning multisensory integration. Neural Networks, 65, pp. 44-52, February, 2015. (Elsevier). Open Access.

 

Degener, O., Häusliche Sturzerkennung mit einem Roboter. eHealth Conference 2014 - Menschen, Metropolen, Möglichkeiten – bessere Versorgung durch eHealth, GVG-Schriftenreihe 75, pp. 210-211, Köln, 2014.

 

Barros, P., Parisi, G. I., Jirak D. and Wermter, S. Real-time Gesture Recognition Using a Humanoid Robot with a Deep Neural Architecture. Proceedings of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), pp. 83-88, Spain, November, 2014.

 

Parisi, G. I., Strahl, E., Wermter, S. Robust Fall Detection with an Assistive Humanoid Robot. 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), November, 2014.

 

Cruz, F., Magg, S., Weber, C., and Wermter, S. Improving Reinforcement Learning with Interactive Feedback and Affordances. Proceedings of the Fourth Joint IEEE ICDL-EpiRob 2014, pp. 125-130, Genoa, Italy, 2014.

 

Bauer, J., Dávila-Chacón, J., Wermter, S. Modeling development of natural multi-sensory integration using neural self-organisation and probabilistic population codes. Connection Science, pp. 1-19, Taylor & Francis, London, October, 2014. Open Access.

 

Borghetti Soares, M., Barros, P., Wermter, S. Learning Objects From RGB-D Sensors for Cleaning Tasks Using a Team of Cooperative Humanoid Robots. Proceedings of 15th Towards Autonomous Robots, TAROS 2014, LNAI 8717, pp. 273-274, Springer Heidelberg. Birmingham, UK, October 1-3, 2014.

 

Parisi, G.I., Weber, C., Wermter, S. Human Action Recognition with Hierarchical Growing Neural Gas Learning. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 89-96, Springer Heidelberg. Hamburg, DE, September 2014.

 

Müller, S., Weber, C., Wermter, S. RatSLAM on Humanoids - A Bio-Inspired SLAM Model Adapted to a Humanoid Robot. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 789-796, Springer Heidelberg. Hamburg, DE, September 2014.

 

Hinaut, X., Wermter, S. An Incremental Approach to Language Acquisition: Thematic Role Assignment with Echo State Networks. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 33-40, Springer Heidelberg. Hamburg, DE, September 2014.

 

Heinrich, S., Wermter, S. Interactive Language Understanding with Multiple Timescale Recurrent Neural Networks. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 193-200, Springer Heidelberg. Hamburg, DE, September 2014.

 

Dávila-Chacón, J., Twiefel, J., Liu, J., Wermter, S. Improving Humanoid Robot Speech Recognition with Sound Source Localisation. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 619-626, Springer Heidelberg. Hamburg, DE, September 2014.

 

Barros, P., Magg, S., Weber, C., Wermter, S. A Multichannel Convolutional Neural Network for Hand Posture Recognition. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 403-410, Springer Heidelberg. Hamburg, DE, September 2014.

 

Wermter, S., Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P., Magg, S., Palm, G., Villa, A.E.P. (Eds.) Artificial Neural Networks and Machine Learning -- ICANN 2014, 24th International Conference on Artificial Neural Networks, Springer Heidelberg, 2014.

 

Heinrich, S., Magg, S., Wermter, S. Analysing the Multiple Timescale Recurrent Neural Network for Embodied Language Understanding. In Koprinkova-Hristova, P.D., et al., editors. Artificial Neural Networks - Methods and Applications, SSBN 4, pp. 149-174, Springer International Publishing, 2014.

 

Parisi, G.I., Jirak, D., Wermter, S. HandSOM - Neural Clustering of Hand Motion for Gesture Recognition in Real Time. In Vargas, P.A., et al., editors. Proceedings of the IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN’14), pp. 981-986, Springer Heidelberg. Edinburgh, Scotland, UK, August 2014.

 

Rubruck, A., Aminian, A., Yalpi, J., Hanzal, P., Winde, S., Kuppusami, S., Younis, S., Thomas, S., Strahl, E., Bauer, J., Dávila-Chacón, J., Heinrich, S., Wermter, S. CoCoCo, Coffee Collecting Companion. In Brodley C.E. et al., editors, Proceedings of the 8th AAAI Video Competition at the 28th AAAI Conference on Artificial Intelligence (AAAI-14), AAAI Press. Québec, CA, 2014. - Nominated in the category for Best Robot Video Award

 


Twiefel, J., Baumann, T., Heinrich, S., Wermter, S. Improving Domain-independent Cloud-based Speech Recognition with Domain-dependent Phonetic Post-processing. In Brodley C.E. et al., editors, Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), pp. 1529-1535, AAAI Press. Québec, CA, 2014.

 

Parisi, G. I., Strahl, E., Wermter, S. Häusliche Sturzerkennung mit einem mobilen Roboter, Presentation at the eHealth Conference, Hamburg, 2014.

 

Wermter, S., Bauer, J., Davila Chacon, J. Sound Source Localization and Multimodal Integration with the iCub head. Proceedings of the "iCub Workshop on Open Source Robotics" at the IEEE International Conference on Robotics and Automation (ICRA), 2014.

 

Parisi, G. I., Barros, P.,Wermter, S. FINGeR: Framework for Interactive Neural-based Gesture Recognition. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN '14), pp. 443-447, Bruges, Belgium, 2014.

 

Johnson, D., Cuijpers, R., Juola, J., Torta, E., Simonov, M., Frisiello, A., Bazzani, M., Yan, W., Weber, C., Wermter, S., Meins, N., Oberzaucher, J., Panek, P., Edelmayer, G., Mayer, P. and Beck, C. Socially-Assistive Robots: A comprehensive approach to extending independent living. In Garcia-Rodriguez. International Journal of Social Robotics, Vol. 6, Issue 2, pp. 195-211, Springer, April 2014.

 

Zhong, J., Cangelosi, A., Wermter, S. Towards a Self-organizing Pre-symbolic Neural Model Representing Sensorimotor Primitives, Frontiers in Behavioral Neuroscience, Vol. 8, Article 22, pp. 1-11, 10.3389/fnbeh.2014.00022, 2014. Open Access.

 

Hamester, D., Jirak, D., Wermter, S. Improved Estimation of Hand Postures Using Depth Images. Proceedings of the 16th International Conference on Advanced Robotics (ICAR 2013), Montevideo, UY, November 2013.

 

Heinrich, S., Weber, C., Wermter, S. Embodied Language Understanding with a Multiple Timescale Recurrent Neural Network. Proceedings of the 23rd International Conference on Artificial Neural Networks (ICANN 2013), LNCS 8131, pp. 216-223, Springer Heidelberg. Sofia, BG, September 2013.

 

Yan, W., Weber, C., Wermter, S. Learning indoor robot navigation using visual and sensorimotor map information. Frontiers in Neurorobotics, Vol. 7, Issue 15, pp. 1-14, 10.3389/fnbot.2013.00015, 2013. Open Access.

 

Dávila-Chacón, J., Magg, S., Liu, J., Wermter, S. Neural and Statistical Processing of Spatial Cues for Sound Source Localisation. Proceedings of International Joint Conference on Neural Networks (IJCNN 2013), pp. 1274–1281, IEEE. Dallas, US, August 2013.

 

Parisi, G., Wermter, S. Hierarchical SOM-Based Detection of Novel Behavior for 3D Human Tracking. Proceedings of International Joint Conference on Neural Networks (IJCNN 2013), pp. 1380–1387, IEEE. Dallas, US, August 2013.

 

Meins, N., Magg, S., Wermter, S. Neural Hopfield-ensemble for multi-class head pose detection. Proceedings of International Joint Conference on Neural Networks (IJCNN 2013), pp. 1327–1334, IEEE. Dallas, US, August 2013.

 

Bauer, J., Wermter, S. Self-Organized Neural Learning of Statistical Inference from High-Dimensional Data. International Joint Conference on Artificial Intelligence (IJCAI-13), pp. 1226–1232, AAAI Press. Beijing, CN, August 2013.

 

Bauer, J., Wermter, S. Learning Multi-Sensory integration with Self-Organization and Statistics. Garcez, A., Lamb, L., Hitzler, P. (Editors), Ninth International Workshop on Neural-Symbolic Learning and Reasoning (NeSy’13), pp. 7–12, Beijing, August 2013.

 

Tripathi, N., Oakes, M., Wermter, S. Hybrid classifiers based on semantic data subspaces for two-level text categorization. International Journal of Hybrid Intelligent Systems, Vol. 10, Issue 1, pp. 33–41, IOS Press Amsterdam, doi:10.3233/HIS-130163, 2013.

 

Yan, W., Torta, E., van der Pol, D., Meins, N., Weber, C., Cuipers, R.H., Wermter, S. Learning Robot Vision for Assisted Living. In Garcia-Rodriguez, J., Cazorla, M., editors. Robotic Vision: Technologies for Machine Leaning and Vision Applications, ch. 15, pp. 257-280, IGI Global, 2013.

 

Kleesiek, J., Badde, S., Wermter, S., Engel, A.K. Action-Driven Perception for a Humanoid. Agents and Artificial Intelligence, Revised Selected Papers of the 4th International Conference on Agents and Artificial Intelligence (ICAART 2012), pp. 83-99, Springer Berlin, doi:10.1007/978-3-642-36907-0_6, January 2013.

 

Zhong, J., Weber, C., Wermter, S. A Predictive Network Architecture for a Robust and Smooth Robot Docking Behavior. Paladyn. Journal of Behavioral Robotics, Vol. 3 (4), pp. 172-180, Springer, 2012.

 

Heinrich, S., Folleher, P., Springstübe, P., Strahl, E., Twiefel, J., Weber, C., Wermter, S. Object Learning with Natural Language in a Distributed Intelligent System - A Case Study of Human-Robot Interaction. Proceedings of the IEEE First International Conference on Cognitive Systems and Information Processing (CSIP 2012), AISC 215, 8 pp. , Springer Berlin. Beijing, CN, December 2012.

 

Meins, N., Jirak, D., Weber, C., Wermter, S. Adaboost and Hopfield Neural Networks on Different Image Representations for Robust Face Detection. Proceedings of the 12th International Conference on Hybrid Intelligent Systems (HIS 2012), pp. 531-536, IEEE. Pune, IN, December 2012.

 

Stramandinoli, F., Cangelosi, A., Wermter, S. Special issue on advances in developmental robotics (Editorial). Paladyn. Journal of Behavioral Robotics, Vol. 3, Issue 3 , pp. 112, doi:10.2478/s13230-013-0112-x, Springer, September 2012.

 

Bauer, J., Dávila-Chacón, J., Strahl, E., Wermter, S. Smoke and Mirrors - Virtual Realities for Sensor Fusion Experiments in Biomimetic Robotics. Proceedings of the 2012 IEEE International Conference on Multisensor Fusion and Information Integration (MFI 2012), pp. 114-119, IEEE. Hamburg, DE, September 2012.

 

Heinrich, S., Weber, C., Wermter, S. Adaptive Learning of Linguistic Hierarchy in a Multiple Timescale Recurrent Neural Network. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 555-562, Springer. Lausanne, CH, September 2012.

 

Zhong, J., Weber, C., Wermter, S. Learning Features and Predictive Transformation Encoding Based on a Horizontal Product Model. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 539-546, Springer. Lausanne, CH, September 2012.

 

Meins, N., Wermter, S., Weber, C. Hybrid Ensembles Using Hopfield Neural Networks. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 403-410, Springer Heidelberg. Lausanne, CH, September 2012.

 

Dávila-Chacón, J., Heinrich, S., Liu, J., Wermter, S. Biomimetic Binaural Sound Source Localisation with Ego-Noise Cancellation. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 239-246, Springer. Lausanne, CH, September 2012.

 

Bauer, J., Weber, C., Wermter, S. A SOM-Based Model for Multi-Sensory Integration in the Superior Colliculus. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), pp. 3245-3252, IEEE. Brisbane, AU, June 2012.

 

Yan, W., Weber, C., Wermter, S. A Neural Approach for Robot Navigation based on Cognitive Map Learning. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), pp. 1146-1153, IEEE. Brisbane, AU, June 2012.

 

Navarro, N., Lowe, R., Wermter, S. A neurocomputational amygdala model of auditory fear conditioning: A hybrid system approach. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), pp. 214-221, IEEE. Brisbane, AU, June 2012.

 

Navarro, N., Weber, C., Schroeter, P., Wermter, S. Real-world reinforcement learning for autonomous humanoid robot docking. Robotics and Autonomous Systems, Vol. 60, Issue 11, pp. 1400-1407, Elsevier, 2012.

 

Zhong, J., Weber, C. Wermter, S. Learning features and transformations with a predictive horizontal product model. Proceedings of the Sixteenth International Conference on Cognitive and Neural Systems (ICCNS 2012), Boston, US, May 2012.

 

Tripathi, N., Oakes, M., Wermter, S. A Fast Subspace Text Categorization Method Using Parallel Classifiers. Proceedings of the 13th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), LNCS 7182, pp. 132-143, Springer. New Delhi, IN, March 2012.

 

Kleesiek, J., Badde, S., Wermter, S., Engel, A.K. What Do Objects Feel Like? - Active Perception for a Humanoid Robot. Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART 2012), Vol. 1, pp. 64-73, SciTePress. Vilamoura, PT, January 2012.

 

Tripathi, N., Oakes, M., Wermter, S. Hybrid Classifiers for Improved Subspace Learning of News Documents. Proceedings of the 11th International Conference on Hybrid Intelligent Systems (HIS 2011), pp. 28-33, IEEE. Malacca, MY, 2011.

 

Saeb, S., Weber, C. & Triesch, J. Learning the Optimal Control of Coordinated Eye and Head Movements. PLoS Comput Biol, Vol. 7 (11), e1002253, Doi: 10.1371/journal.pcbi.1002253, 2011.

 


Navarro, N., Lowe, R., Weber, C., Wermter, S. Many-routes hypothesis of fear conditioning: a dynamical reservoir based approach. Marie-Curie Researchers Symposium Poster, Warsaw, PL, September 2011.

 

Heinrich, S., Wermter, S. Towards Robust Speech Recognition for Human-Robot Interaction. Proceedings of the IROS2011 Workshop on Cognitive Neuroscience Robotics (CNR), pp. 29-34, San Francisco, CA, USA, September 2011.

 

Zhong, J., Weber, C. Wermter, S. Restricted Boltzmann Machine with Transformation Units in a Mirror Neuron System Architecture. Proceedings of the IROS2011 Workshop on Cognitive Neuroscience Robotics (CNR), pp. 23-28, San Francisco, CA, USA, September 2011.

 

Navarro, N., Weber, W., Wermter, S. Real-world reinforcement learning for autonomous humanoid robot charging in a home environment. Proceedings of the 12th Annual Conference Towards Autonomous Robotic Systems (TAROS 2011), LNCS Vol. 6856, pp. 231-240, Springer Berlin/Heidelberg. Sheffield, UK, August 2011.

 

Kleesiek, J., Weber, C., Wermter, S., Engel, A.K. Reward-Driven Learning of Sensorimotor Laws and Visual Features. Proceedings of the 1st Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, Vol. 2, pp. 1-6, IEEE. Frankfurt, DE, August 2011.

 

Yan, W., Weber, C., Wermter, S. A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera. Ambient Intelligence and Smart Environments, Vol. 3 (3), pp. 237-252, IOS Press Amsterdam, 2011. Open Access.

 

Tripathi, N., Oakes, M., Wermter, S. Semantic subspace learning for text classification using hybrid intelligent techniques. International Journal of Hybrid Intelligent Systems, Vol. 8 (2), pp. 99-114, IOS Press Amsterdam, 2011.

 

Yan, W., Weber, C., Wermter, S. Person tracking based on a hybrid neural probabilistic model. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), LNCS 6792, Part II, pp. 365-372, Springer. Espoo, FI, June 2011.

 

Zhong, J.P., Weber, C., Wermter, S., Robot Trajectory Prediction and Recognition based on a Computational Mirror Neurons Model. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), LNCS 6792, Part II, pp. 333-340, Springer. Espoo, FI, June 2011.

 

Tripathi, N., Oakes, M., Wermter, S. Hybrid Parallel Classifiers for Semantic Subspace Learning. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), LNCS 6792, Part II, pp. 64-70, Springer. Espoo, FI, June 2011.

 

Heinrich, S., Eberling, M., Wermter, S. Determining Cooperation in Multiagent Systems with Cultural Traits. Proceedings of the 3rd International Conference on Agents and Artificial Intelligence (ICAART 2011), Vol. 2, pp. 173-180, SciTePress. Rome, IT, January 2011.

 

Knowles, M., Baglee, D., Wermter, S. Reinforcement Learning for Scheduling of Maintenance. Proceedings of the 30th International Conference on Artificial Intelligence (SGAI 2010), pp. 409-422, Springer. Cambridge, England, UK, December 2010.

 

Liu J., Perez-Gonzalez D., Rees A., Erwin H., Wermter, S. A biologically inspired spiking neural network model of the auditory midbrain for sound source localisation. Neurocomputing. Vol. 74, pp. 129-139, Elsevier, 2010.

 

Kleesiek J., Engel A.K., Wermter, S., Weber C. Object Affordances in the Context of Sensory Motor Contingencies. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience, Frontiers. Berlin, DE, September 2010.

 


Jirak, D., Menz, M.M., Buccino, G., Borghi, A., Binkofski, F. Grasping language - A short story on embodiment. Consciousness & Cognition. Vol. 19 (3), pp. 711-720, Elsevier, 2010.

 

Yau C. Y., Burn K., Wermter, S. Configuring the Stochastic Helmholtz Machine for Subcortical Emotional Learning. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), pp. 1384-1391, IEEE. Barcelona, ES, July 2010.

 

Tripathi N., Wermter, S., Hung C., Oakes, M. Semantic Subspace Learning with Conditional Significance Vectors. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), pp. 3670-3677, IEEE. Barcelona, ES, July 2010.

 

Zhong, J.P., Fung, Y.F., Dai M.J. A biologically inspired improvement strategy for particle filter: Ant colony optimization assisted particle filter. International Journal of Control, Automation, and Systems, vol. 8 (3), pp. 519-526, Springer, 2010.

 

Anwar, M. N., Oakes, M. P., Wermter, S. and Heinrich, S. Clustering Audiology Data. In Ramon, J., Vens, C., Driessens, K., Van Otterlo, M., Vanschoren, J., editors. Proceedings of the 19th Annual Belgian-Dutch Conference on Machine Learning (BeneLearn 2010), Leuven, BE, May 2010.

 

Liu, J., Perez-Gonzalez, D., Rees, A., Erwin, H. and Wermter, S. Multiple Sound Source Localisation in Reverberant Environments Inspired by the Auditory Midbrain. Artificial Neural Networks -ICANN 2009, Part I, LNCS 5768, pp. 208-217, 2009

 

Ravulakollu, K., Knowles, M., Liu, J., Wermter, S. Towards Computational Modelling of Neural Multimodal Integration Based on the Superior Colliculus Concept. Innovations in Neural Information Paradigms and Applications, Vol. 247, Springer Berlin / Heidelberg, pp. 269-291, 2009

 

Muse, D., Wermter, S. Actor-Critic Learning for Platform-Independent Robot Navigation. Cognitive Computation, Vol. 1, Springer New York, pp. 203-220, 2009

 

Liu, J., Perez-Gonzalez, D., Rees, A., Erwin, H. and Wermter, S. A Biomimetic Spiking Neural Network of the Auditory Midbrain for Mobile Robot Sound Localisation in Reverberant Environments. International Joint Conference on Neural Networks (June 2009), pp. 1855-1862, Atlanta, USA.

 

Wermter, S., Page, M., Knowles, M., Gallese, V., Pulvermüller, F., Taylor, J. Multimodal communication in animals, humans and robots: An introduction to perspectives in brain-inspired informatics. Neural Networks 22 (2009), pp. 111-115. Journal homepage: www.elsevier.com/locate/neunet

 

Murray, J., Erwin, H., Wermter, S. Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks. Neural Networks 22 (2009), pp. 173-189. Journal homepage: www.elsevier.com/locate/neunet

 

Liu, J., Erwin, H., Wermter, S. Mobile Robot Broadband Sound Localisation Using a Biologically Inspired Spiking Neural Network. IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS 2008), pp. 2191-2196. Nice, France, September, 22-26th, 2008.

 

Erwin, Harry R., Elshaw, Mark I., Wermter, S., Perez-Gonzalez, D., Rees, A. Second International Conference on Acoustic Communication by Animals, Corvallis, Oregon, August 2008

 

Liu, J., Perez-Gonzalez, D., Rees, A.,Erwin, H., Wermter, S. Robot Sound Localisation Neural Network Inspired by the Inferior Colliculus. British Society of Audiology Meeting on Experimental Studies of Hearing and Deafness, York University, August 2008

 

Official Newsletter of the Natural Computing Applications Forum Edition 54. An invitation from intelligent robots. December, 2008

 

Liu, J., Erwin, H., Wermter, S. Mobile Robot Broadband Sound Localisation Using a Biologically Inspired Spiking Neural Network. IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS 2008), pp. 2191-2196. Nice, France, September, 22-26th, 2008.

 

Liu, J., Erwin, H., Wermter, S. and Elsaid, M. A Biologically Inspired Spiking Neural Network for Sound Localisation by the Inferior Colliculus. Artificial Neural Networks - ICANN 2008, vol. 5164/2008, pp. 396-405, August 2008.

 

Murray, J.C, Wermter, S. and Knowles, M.J. MIRA: A Learning Multimodal Interactive Robot Agent. 8th International Conference on Hybrid Intelligent Systems. Barcelona, Spain, September 10-12th, 2008.

 

Knowles, M.J. and Wermter, S. The Hybrid Integration of Perceptual Symbol Systems and Interactive Reinforcement Learning. 8th International Conference on Hybrid Intelligent Systems. Barcelona, Spain, September 10-12th, 2008.

 

Wermter, S. and HIS group. Hybrid Intelligent Systems. NETWorks - The Science Engineering and Technology magazine for North East England. Medical Devices and Instrumentation. Issue 5, pp. 14-15, Spring, 2008. (Preprint)

 

Hung, C. and Wermter, S. A novel self-organising clustering model for time-event documents. The Electronic Library, vol. 26, no. 2, pp. 260-272. (2008, SSCI).

 

K. K. Kiran Bhagat., Wermter, S. and Burn, K. Hybrid Learning Architecture for Unobtrusive Infrared Tracking Support. International Joint Conference on Neural Networks (IJCNN/WCCI), pp. 2704-2710. Hongkong, June 2008.

 

Yau, C.Y., Burn, K. and Wermter, S. A Neural Wake-Sleep Learning Architecture for Associating Robotic Facial Emotions. International Joint Conference on Neural Networks (IJCNN/WCCI), pp. 2716- 2722. Hongkong, June 2008.

 

Altahhan, A., Burn, K. and Wermter, S. Visual Robot Homing using Sarsa, Whole Image Measure, and Radial Basis Function. International Joint Conference on Neural Networks (IJCNN/WCCI), pp. 3860-3867. Hongkong, June 2008.

 

Bellotto, M., Burn, K., Fletcher, E. and Wermter, S. Appearance-based localization for mobile robots using digital zoom and visual compass, Robotics and Autonomous Systems, Vol. 56, Issue 2, pp. 143-156, February 2008.

 

Weber, C., Elshaw, M., Wermter, S., Triesch J. and Willmot, C. Reinforcement Learning Embedded in Brains and Robots, In: Weber, C., Elshaw M., and Mayer N. M. (Eds.) Reinforcement Learning: Theory and Applications, pp. 119-142, 2008, I-Tech Education and Publishing, Vienna, Austria.

 

Willmot, C., Wermter, S. and Panchev, C. Developing Concepts from Robot Behaviour by Growing Self Organizing Networks. 7th International Conference on Epigenetic Robotics, Piscataway, NJ, 2007.


Erwin, H., Elshaw, M., Rees, A., Perez-Gonzalez, D., Wermter, S. Modeling Regular Firing Neurons of the Inferior Colliculus. International Conference on Cognitive Neurodynamics, Shanghai, 2007.

 

Elshaw, M., Erwin, H., Wermter, S., Perez-Gonzalez, ., Rees, A. Modelled properties of single neurons in the auditory midbrain. IBRO World Congress of Neuroscience, Melbourne, Australia, 12-17 July.

 

Murray, J., Rowan, C., Yau, A., Elshaw, M., Wermter, S. Sound localisation and emotional language communication in the Mira robot head. Proceedings of the AI Video Competition at 22nd AAAI Conference on Artificial Intelligence, 2007.

 

Weber C., Wermter, S. A Self-Organizing Map of Sigma-Pi Units. Neurocomputing. Vol. 7, pp. 2552-2560, 2007. (Elsevier)

 

Hung, C., Chen, J.-H. and Wermter, S.  Hybrid Probability-Based Ensembles for Bankruptcy Prediction. International Conference on Business and Information, July 11-13, 2007, Tokyo, Japan

 

McGarry, K., Garfield S., Wermter, S. Auto Extraction, Representation and Integration of a Diabetes Ontology using Bayesian Networks. Proceedings of the IEEE International Symposium on Computer Based Medical Systems. Maribor, Slovenia, pp. 612-617, 2007.

 

McGarry K., Garfield S., Morris N. and Wermter, S. Integration of Hybrid Bio-Ontologies using Bayesian Networks for Knowledge Discovery. In: Artur S. d'Avila Garcez, Pascal Hitzler, Guglielmo Tamburrini (Eds.), Proceedings of the IJCAI-07 Third International Workshop on Neural-Symbolic Learning and Reasoning, NeSy'07, Hyderabad, India, January 2007.

 

Weber, C., Elshaw, M., Triesch, J. and Wermter, S. Neural Control of Actions Involving Different Coordinate Systems. In Hackel, M., Humanoid Robots: Human-like Machines, pp. 577-600, Itech, Vienna, Austria, June 2007.

 

Erwin, H., Wermter, S., Elshaw, M., Rees, A. MiCRAM - Mibrain computational and robotic auditory model for focused hearing. Auditory Cortex, Cambridge, Sept. 2006


Murray J., Wermter, S., and Erwin, H. Bioinspired auditory sound localization for improving the signal to noise ratio of socially interactive robots. Proceedings of the International Conference on Intelligent Robots and Systems, pp. 1206-1211. Beijing, China. Oct. 2006

 

Muse D., Burn K., and Wermter, S. Reinforcement Learning for Platform-Independent Visual Robot Control. International Joint Conference on Neural Networks, 2006.

 

Garfield S., Wermter, S., Call Classification using Recurrent Neural Networks, Support Vector Machines and Finite State Automata. Knowledge and Information Systems: An International Journal, Vol 9,2, pp. 131-156 2006.

 

Panchev, C., Wermter, S.,  Temporal Sequence Detection with Spiking Neurons: Towards Recognizing Robot Language Instruction. Connection Science, Vol 18,1, pp. 1-22, 2006. 

 

Muse D., Weber C., and Wermter, S. Robot Docking Based on Omnidirectional Vision and Reinforcement Learning. Knowledge-Based Systems, Vol 19, 5, pp. 324-332 2006. (Elsevier)

 

Malone J., McGarry K., Wermter, S., and Bowerman C. Data mining using rule extraction from Kohonen self-organising maps. Neural Computing & Applications, Vol 15, Issue 1, pp. 9-17, 2006.

 

Weber C., Muse D., Elshaw M., and Wermter, S. A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot. Knowledge-Based Systems, 19 (5), 348-355, 2006. (Elsevier)

 

Weber C., Wermter, S., and Elshaw M. A hybrid generative and predictive model of the motor cortex. Neural Networks, 9 (4), pp. 339-353, 2006. (Elsevier)

 

Oakes M P, Cox S. & Wermter, S. Data Mining Audiology Records with the Chi-Squared Test and Self-Organising Maps. 22nd British National Conference on Databases. D. Nelson et al. (Eds. ) pp. 123-130, 2005, University of Sunderland Press.

 

Wermter, S., Palm G., Elshaw M.   Biomimetic Neural Learning for Intelligent Robots, Springer, 2005.

 

Garfield S., Wermter, S., and Devlin S. Spoken Language Classification using Hybrid Classifier Combination. International Journal of Hybrid Intelligent Systems Vol. 2, No.1, pp. 13-33, 2005.

 

Muse D., Weber C., and Wermter, S. Robot Docking Based on Omnidirectional Vision and Reinforcement Learning. Research and Development in Intelligent Systems XXII - International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 23-36, 2005 Springer.

 

Weber C., Muse D., Elshaw M., and Wermter, S. A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot. Applications and Innovations in Intelligent Systems XIII - International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 151-164, 2005 Springer.

 

Weber C., Karantzis K., and Wermter, S. Grasping with flexible viewing-direction with a learned coordinate transformation network. in Proceedings of 5th IEEE-RAS International Conference on Humanoid Robots, pp. 253-258, 2005.

 

Murray J., Erwin H., Wermter, S. A Hybrid Architecture using Cross-Correlation and Recurrent Neural Networks for Acoustic Tracking in Robots. In Wermter, S., Palm G., Elshaw M. Biomimetic Neural Learning for Intelligent Robots, pp. 55-73, 2005.

 

Wermter, S., Weber C., Elshaw M., Gallese, V. Pulvermüller F. Grounding Neural Robot Language in Action. In Wermter, S., Palm G., Elshaw M. Biomimetic Neural Learning for Intelligent Robots, pp. 162-181, 2005.

 

Weber W., Wermter, S. Image Segmentation by Complex-Valued Units. International Conference on Artificial Neural Networks 2005, pp. 305-310, 2005. Springer.

 

Wermter, S., Palm G., Weber C., Elshaw M. Towards Biomimetic Neural Learning for Intelligent Robots. In Wermter, S., Palm G., Elshaw M., . Biomimetic Neural Learning for Intelligent Robots, pp. 1-18, 2005.

 

Weber W., Muse D., Elshaw M., Wermter, S. Reinforcement Learning in MirrorBot. International Conference on Artificial Neural Networks 2005, pp. 305-310, 2005. Springer.

 

Murray J., Erwin H., Wermter, S. Auditory Robotic Tracking of Sound Sources using Hybrid Cross-Correlation and Recurrent Network. International Conference on Intelligent Robots and Systems, 2005.

 

McGarry K., Wermter, S. Training without Data: Knowledge Insertion into RBF Neural Networks. International Joint Conference on Artificial Intelligence, Edinburgh, pp. 792-797, 2005.

 

Murray J., Erwin H., Wermter, S. A Recurrent Neural Network for Sound-Source Motion Tracking and Prediction. International Joint Conference in Neural Networks, pp. 2232-2236, 2005.

 

Hung C., Wermter, S. A Constructive and Hierarchical Self-Organising Model in a Non-Stationary Environment. International Joint Conference in Neural Networks, pp. 2948-2953, 2005.

 

Malone J., Elshaw M., McGarry K., Bowerman C., Wermter, S. Spatio-Temporal Neural Data Mining Architecture in Learning Robots. International Joint Conference in Neural Networks, pp. 2802-2807, 2005.

 

Wermter, S., Weber C., Elshaw M., Associative Neural Models for Biomimetic Multi-modal Learning in a Mirror Neuron-based Robot. In Cangelosi A., Bugmann G. & Borisyuk R. (Eds.). Modeling Language, Cognition and Action. Singapore: World Scientific, pp. 31-46, 2005.

 

Hung C., Wermter, S. Neural Network-based Document Clustering using WordNet Ontologies.   International Journal of Hybrid Intelligent Systems, Vol. 1, pp. 127-142, 2004.

 

Oakes, M., Ant Colony Optimisation for Stylometry: The Federalist Papers. International Conference on Recent Advances in Soft Computing, November 2004.

 

Cox, S., Oakes, M., Wermter, S.and Hawthorne, M, AudioMine: Medical Data Mining in Heterogeneous Audiology Records. International Journal of Computational Intelligence, Vol. 1, pp. 1-12, 2004.

 

Malone, J., McGarry, K. and Bowerman, C., Using an Adaptive Fuzzy Logic System to Optimise Knowledge Discovery in Proteomics. International Conference on Recent Advances in Soft Computing, November 2004, pp. 80-85.

 

Murray J., Erwin H., Wermter, S. Robotics Sound-Source Localization and Tracking using Interaural Time Difference and Cross-Correlation. Proceedings of NeuroBotics. Workshop, Ulm, Germany, pp. 89-97, September 2004.

 

Elshaw M., Weber C.,  Zochios A., Wermter, S. A Mirror Neuron Inspired Hierarchical Network for Action Selection.  Proceedings of NeuroBotics. Workshop, Ulm, Germany, pp. 98-105, September 2004.

 

Weber C., Elshaw M., Zochios A., Wermter, S. A Multimodal Hierarchical Approach to Robot Learning by Imitation.  Fourth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, Genoa, Italy, pp. 131-134, 2004.

 

Weber C., Wermter, S., Zochios A. Robot Docking with Neural Vision and Reinforcement. Knowledge Based Systems, Vol. 12, No. 2-4, pp. 165-72, 2004. 

 

Panchev, C., Wermter, S.,  Spike-timing-dependent Synaptic Plasticity: From Single Spikes to Spike Trains. Neurocomputing, Vol. 58-60, pp. 365-371, 2004. 

 

Elshaw M., Weber C., Zochios A., Wermter, S. An Associator Network Approach to Robot Learning by Imitation through Vision, Motor Control and Language.   Proceedings of the International Joint Conference on Neural Networks. pp. 591-596, Budapest, Hungary, July 2004.

 

Hung C., Wermter, S. A Time-Based Self-Organising Model for Document Clustering.   Proceedings of the International Joint Conference on Neural Networks, pp. 17-23, Budapest, Hungary, July 2004.

 

Wermter, S., Weber C., Elshaw M., Panchev, C., Erwin H., Pulvermüller F., Towards Multimodal Neural Robot Learning. Robotics and Autonomous Systems Journal, . Vol. 47, No. 2-3, pp. 171-175, 2004.

 

Hung C., Wermter, S., Smith P. Predictive Top-down Knowledge Improves Neural Exploratory Bottom-up Clustering. Proceedings of ECIR’04 European Conference on Information Retrieval, Sunderland, UK, pp. 154-166, 5-7, April 2004.

 

Addison J.  McGarry K. Wermter, S. MacIntyre, J.  Stepwise Linear Regression Dimensionality Reduction in Neural Network Modelling. Proceedings of the International Conference on Artificial Intelligence and Applications, pp. 363-368, Innsbruck, Austria, February 2004.

 

Hung C., Wermter, S., Smith P. Hybrid Neural Document Clustering Using Guided Self-organisation and WordNet. Issue of IEEE Intelligent Systems, pp. 68-77, March/April 2004, © 2004 IEEE.

 

Panchev, C., Wermter, S. Spiking-time-dependent Synaptic Plasticity: From Single Spikes to Spike Trains. Proceedings of the Computational Neuroscience Meeting , Alicante, Spain, July 2003.

 

Hung C., Wermter, S. A Self-Organising Hybrid Model for Dynamic Text Clustering. Proceedings of the The Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK, December, pp. 141-154 2003.

 

Hung C., Wermter, S., A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering. Proceedings of The Third IEEE International Conference on Data Mining, pp. 75-82, Melbourne, USA, 2003. 

 

Garfield, S, Wermter, S., Recurrent Neural Learning for Classifying Spoken Utterances. Expert Update, Special Issue on Neural Language Processing, Vol. 6, No. 3, pp. 31-36, 2003. 

 

Wermter, S., Elshaw M., Weber C., Panchev, C., Erwin  H. Towards Integrating Learning by Demonstration and Learning by Instruction in a Multimodal Robotics. Proceedings of the IROS-2003 Workshop on Robot Learning by Demonstration, pp. 72-79, October 2003.

 

Weber C., Wermter, S., Zochios A. Robot Docking with Neural Vision and Reinforcement. Proceedings of the The Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence , Cambridge, UK, December 2003.

 

Elshaw M., Lewis D., Wermter, S. Incorporating Reactive Learning Behaviour into a Mini-robot Platform. Proceedings of the The Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK, December, pp. 255-266, 2003.

 

Arevian, G., Wermter, S., Panchev, C. Symbolic State Transducers and Recurrent Neural Preference Machines for Text Mining. International Journal on Approximate Reasoning, Vol. 32, No. 2/3, pp. 237-258, 2003. Elsevier

 

Wermter, S., Elshaw M., Farrand S.  A Modular Approach to Self-organisation of Robot Control Based on Language Instruction. Connection Science, Vol. 15, No 2-3, pp. 73-94,  2003.

 

Garfield, S., Wermter, S. Comparing State Vector Machines, Recurrent Networks and Finite State Transducers for Classifying Spoken Utterances. International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 646-653, June, 2003.

 

Weber C., Wermter, S. Object Locialisation using Laterally Connected "What" and "Where" Associator Networks. Proceedings of the International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 813-820, June 2003.

 

Addison D., Wermter, S., Arevian, G. A Comparison of Feature Extraction and Selection Techniques. Proceedings of the International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 212-215, June 2003.

 

Wermter, S., Elshaw M. Learning Robot Actions Based on Self-organising Language Memory. Neural Networks, Vol. 16, No. 5-6, pp. 691-699, 2003.

 

Elshaw M., Wermter, S., Watt P. Self-organisation of Language Instruction for Robot Action. Proceedings of the International Joint Conference on Neural Networks. Oregon, USA, pp. 22-27, July 2003.

 

Garfield S., Wermter, S. Recurrent Neural Learning for Helpdesk Call Routing. Proceedings of the International Conference on Artificial Neural Networks, Madrid, Spain, pp. 296-301, August 2002.

 

Wermter, S., Hung C. Selforganizing Classification on the New Reuters News Corpus. Proceedings of the International Conference on Computational Linguistics, Taipei, Taiwan, pp. 1086-1092, August 2002.

 

Addison D., Wermter, S., McGarry K., Macintyre J. Methods for Integrating Memory into Neural Networks in Condition Monitoring. Proceedings of the International Conference on Artificial Intelligence and Soft Computing, Banff, Alberta, Canada, pp. 380-384, July 2002.

 

Panchev, C., Wermter, S., Chen H. Spike-timing Dependant Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites. Proceedings of the International Conference on Artificial Neural Networks, pp. 896-901, August 2002.

 

Womble, S., Wermter, S. and Treves A. Information Processing in Layer 4: A Tabula Rasa?. Proceedings of the Sixth International Conference on Cognitive and Neural Systems, May 2002.

 

Wermter, S., Panchev, C. Hybrid Preference Machines based on Inspiration from Neuroscience. Cognitive Systems. Research. Vol. 3, No. 2, pp. 255-270, 2002. Elsevier

 

Elshaw, M., Wermter, S. A Neurocognitive Approach to Self-organisation of Verb Actions. Proceedings of the International Joint Conference on Neural Networks. Honolulu, USA, pp. 24-29, May 2002.

 

Womble, S., Wermter, S. Mirror Neurons and Feedback Learning. In Stamenov, M. I. and Gallese, V. Mirror Neurons and the Evolution of Brain and Language. John Benjamins Publishing Company, Amsterdam, pp. 353-362, 2002.

 

Panchev, C., Wermter, S. Hebbian Spike-Timing Dependent Self-Organization in Pulse Neural Networks. Proceedings of World Congress on Neuroinformatics. Vienna, Austria, pp. 378-385, September 2001.

 

Addison D., Wermter, S., and Macintyre J. Multilayer Perceptrons and Radial Basis Function Networks for Corrosion Monitoring. Proceedings of the International Conference on Artificial Intelligence and Applications . Marbella, September 2001, pp. 77-81.

 

McGarry K., Wermter, S., MacIntyre, J. The Extraction and Comparison of Knowledge From Local Function Networks. International Journal of Computational Intelligence and Applications, Vol. 1, Issue 4, pp. 369-382, 2001.

 

Wermter, S., Austin, J., Willshaw, D. Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany. 2001.

 

Wermter, S., Austin, J., Willshaw, D., Elshaw M. Towards Novel Neuroscience-inspired Computing. In Wermter, S., Austin, J. and Willshaw, D. Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany, pp. 1-19, 2001.

 

Womble, S., Wermter, S. A Mirror Neuron System for Syntax Acquisition. Proceedings of International Conference on Artificial Neural Networks. Vienna, Austria, August 2001, pp. 1213-1219.

 

Garfield S., Elshaw M., Wermter, S. Self-Organising Networks for Classification Learning from Normal and Aphasic Speech. Proceedings of the 23rd Conference of the Cogntive Science Society. Edinburgh, Scotland, August 2001, pp. 319-324.

 

McGarry K., Wermter, S., Macintyre, J. Knowledge Extraction from Local Function Networks. Proceedings of the International Joint Conference on Artificial Intelligence. Seatle, August 4-10 2001.

 

Wermter, S., Arevian, G. Modular Preference Moore Machines in News Mining Agents. Proceedings of the Joint 9th International Fuzzy Systems Association World Congress and the 20th North American Fuzzy Information Processing Society International Conference. Vancouver, Canada, pp. 1786-1792, July 2001.

 

Garfield S. Review of: Speech and Language Processing. Cognitive Systems Research, Vol. 2, No. 2, pp. 167-172, 2001. Elsevier

 

Wermter, S., Sun, R. The Present and the Future of Hybrid Symbolic Systems. AI Magazine. Spring, pp. 123-126. 2001.

 

Wermter, S. The Hybrid Approach to Artificial Neural Network-based Language Processing. In: Dale R., Moisl H. and Somers H. (Ed.). Handbook of Natural Language Processing, pp. 823-846. Marcel Dekker. 2000.

 

Panchev, C., Wermter, S. Sequential Processing in Neuroscience Inspired Models. Proceedings of Third International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience, pp. 84-88. Durham, UK, August 2000.

 

Wermter, S., Panchev, C. Hybrid Sequential Machines based on Neuroscience. Proceedings of the ECAI Workshop on Foundations of Connectionist Symbolic Integration, pp. 13-24. Berlin, Germany, August 2000.

 

Wermter, S. Neural Network Agents for Learning Semantic Text Classification. Information Retrieval. Vol. 3, No. 2, pp. 87-103. 2000.

 

Wermter, S. Neural Fuzzy Preference Integration using Neural Preference Moore Machines. International Journal of Neural Systems. Vol. 10, No. 4, pp. 287-309, 2000.

 

Wermter, S., Austin, J., Willshaw, D. International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience, Durham, UK, 7-8 August 2000.

 

Wermter, S., Arevian, G., Panchev, C. Meaning Spotting and Robustness of Recurrent Networks. Proceedings of the International Joint Conference on Neural Networks, pp. III-433-438. Como, Italy, July 2000.

 

Panchev, C., Wermter, S. Complex Preferences for the Integration of Neural Codes. Proceedings of the International Joint Conference on Neural Networks, pp. III-433-258. Como, Italy, July 2000.

 

Womble, S., Wermter, S. Language Acquisition in the Brain Using Reinforcement Learning Agents. Proceedings of the International Conference on Mirror Neurons and the Evolution of Brain and Language. Delmenhorst, Germany, July 2000.

 

Wermter, S., Sun, R. Hybrid Neural Systems. Springer, Heidelberg, Germany. 2000.

 

Wermter, S., Arevian, G., Panchev, C. Network Analysis in a Neural Learning Internet Agents. Proceedings of the International Conference on Computer Intelligence and Neuroscience, pp. 880-884, Atlantic City, USA, March 2000.

 

Wermter, S. Knowledge Extraction from Transducer Neural Networks. Journal of Applied Intelligence, Vol. 12, pp. 27-42. 2000.

 

Wermter, S., Arevian, G., Panchev, C. Towards Hybrid Neural Learning Internet Agents. In: Wermter, S., Sun, R. (Ed.) Hybrid Neural Systems, pp. 160-176. Springer, Heidelberg, Germany. 2000.

 

Wermter, S., Austin, J., Willshaw, D. International Workshop on Emergent Neural Computational Architectures Based on Neuroscience. Edinburgh, UK, 11 September 1999.

 

McGarry K., Tait, J., Wermter, S., MacIntyre, J. Rule Extraction from Radial Basis Function Networks. Proceedings of the International Conference on Artificial Neural Networks, pp. 613-618, Edinburgh, UK, September 1999.

 

Wermter, S., Arevian, G., Panchev, C. Recurrent Neural Network Learning for Text Routing. Proceedings of the International Conference on Artificial Neural Networks, pp. 898-903, Edinburgh, UK, September 1999.

 

Addison D., Wermter, S., MacIntyre, J. Effectiveness of Feature Extraction in Neural Network Architectures for Novelty Detection. Proceedings of the International Conference on Artificial Neural Networks, pp. 976-981, Edinburgh, UK, September 1999.

 

Wermter, S. Preference Moore Machines for Neural Fuzzy Integration. Proceedings of the International Joint Conference on Artificial Intelligence, pp. 840-845, Stockholm, Sweden, August 1999.

 

Wermter, S., Austin, J., Willshaw, D. Workshop on Neuroscience and Neural Computation. Orlando, Florida, USA, 19 July 1999.

 

Wermter, S., Panchev, C., Houlsby, J. Language Disorders in the Brain: Distinguishing Aphasia Forms with Recurrent Networks. Proceedings of AAAI*99 Conference Workshop on Neuroscience and Neural Computation, pp. 93-98, Orlando, USA, July 1999.

 

McAlister M., Wermter, S. Rule Generation from Neural Networks for Student Assessment. Proceedings of the International Joint Conference on Neural Networks, paper 455, Washington, USA, July 1999.

 

McGarry K., Wermter, S., MacIntyre, J. Knowledge Extraction from Radial Basis Function Networks and Multi-layer Perceptrons. Proceedings of the International Joint Conference on Neural Networks, Washington, USA, July 1999.

 

Wermter, S., Panchev, C. Arevian, G. Hybrid Neural Plausibility Networks for News Agents. Proceedings of the National Conference on Artificial Intelligence AAAI, pp. 93-98, Orlando, USA, July 1999.

 

McGarry K., Wermter, S., MacIntyre, J. Knowledge Transfer Between Radical Basis Function Networks. Proceedings of Conference on Cognitive Science for the New Millennium, Dublin, Ireland, May 1999.

 

McGarry K., Wermter, S., MacIntyre, J. Hybrid Neural Systems: From Simple Coupling to Fully Integrated Neural Networks. Neural Computing Surveys, Vol. 2., pp. 62-94. 1999.

 

Wermter, S., Sun, R. Nips Workshop on Hybrid Neural Symbolic Integration. Breckenridge, Colorado, USA, 1998.

 

Wermter, S. Lazy Neural Network Learning for Building Symbolic Transducers. Proceedings of the International Conference on Computational Intelligence and Neuroscience, Research Triangle Park, North Carolina, USA, 1998.

 

Wermter, S. Hybrid Neural Symbolic Agent Architectures for Multimedia. Proceedings of the IEE Colloquium on Neural Network in Interactive Multimedia Systems, London, 1998.

 

Chen J., Wermter, S. Continuous Time Recurrent Neural Networks for Grammatical Induction. Proceedings of the International Conference on Artificial Neural Networks, pp. 381-386, Skovde, Sweden, 1998.

 

Wermter, S. Hybrid Neural and Symbolic Language Processing. Proceedings of the Interdisciplinary Conference, Guenne, Germany, 1998.

 

Wermter, S. Hybrid Approaches to Neural Network-based Language Processing. International Computer Science Institute. Technical Report, Berkeley, CA, 1997, TR-97-030.

 

Wermter, S., Meurer M. Building Lexical Representations Dynamically Using Artificial Neural Networks. Proceedings of the International Conference of the Cognitive Science Society, pp. 802-807, Stanford, 1997.

 

Wermter, S., Chen J. Cautious Steps towards Hybrid Connectionist Bilingual Phrase Alignment. Proceedings of the Conference on Recent Advances in Natural Language Processing, pp. 364-368, Sofia, Bulgaria, 1997.

 

Wermter, S., Weber, V. SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks. Journal of Artificial Intelligence Research, Vol. 6, No. 1, pp. 35-85. 1997.

 

Wermter, S., Hannuschka R. A Connectionist Model for the Interpretation of Metaphors. In: Dorffner G. (Ed.) Neural Networks and a New AI, pp. 255-276, Thomson International, 1997.

 

Wermter, S. Riloff, E. Scheler, G. (Ed). Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. Springer Verlag, Berlin. 1996.

 

Wermter, S., Weber, V. Interactive Spoken-Language Processing in a Hybrid Connectionist System SCREEN. IEEE Computer Journal, pp. 65-74, July 1996.

 

Wermter, S., Löchel M. Learning Dialog Act Processing. Proceedings of the International Conference on Computational Linguistics, pp. 740-745, Kopenhagen, Denmark, 1996.

 

Wermter, S., Meurer M. Towards Constructive and Destructive Dynamic Network Configuration. Proceedings of the European Symposium on Artificial Neural Networks, Brugge, Belgium, 1996.

 

Weber V., Wermter, S. Using Hybrid Connectionist Learning for Speech/Language Analysis. In S. Wermter, E. Riloff, G. Scheler (Ed.) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing, pp. 87-101, Springer Verlag, Berlin. 1996.

 

Wermter, S., Weber V. Artificial Neural Networks for Automatic Knowledge Acquisition in Multiple Real-World Language Domains. In. Proceedings of the 8th International Conference on Neural Networks and their Applications, pp. 289-296, Marseilles, FRA, 1995.

 

Weber V., Wermter, S. Artificial Neural Networks for Repairing Language. In Proceedings of the 8th International Conference on Neural Networks and their Applications. Marseilles, FRA, 1995.

 

Weber V., Wermter, S. Towards Learning Semantics of Spontaneous Dialog Utterances in a Hybrid Framework. In: J. Hallam (Ed.) Hybrid Problems, Hybrid Solutions, pp. 229-238, IOS Press, Amsterdam. 1995.

 

Wermter, S. Ein Spektrum hybrider konnektionistischer Architekturen im Vergleich mit SCREEN. University of Hamburg, VM-Memo 66. 1995.

 

Wermter, S. Hybrid Connectionist Natural Language Processing. Chapman and Hall, International Thomson Computer Press, London, UK, January, 1995.

 

Wermter, S., Weber V. Learning Fault-Tolerant Speech Parsing with SCREEN. In Twelfth National Conference on Artificial Intelligence. pp. 670-675, Seattle, Washington, July/August 1994.

 

Wermter, S., Löchel M. Connectionist learning of flat syntactic analysis for speech/language systems. Proceedings of the International Conference on Artificial Neural Networks, pp. 941-944, Sorrento, Italy, 1994.

 

Wermter, S. Learning Natural Language Filtering Under Noisy Conditions. Proceedings of the Tenth IEEE Conference on Artificial Intelligence for Applications, pp. 215-221, San Antonio, USA, 1994.

 

Wermter, S. Incremental Connectionist Architectures for Language Learning. VM-Memo 7, University of Hamburg, Hamburg, FRG, 1994.

 

Wermter, S. Hybride Symbolische und Subsymbolische Verarbeitung am Beispiel der Sprachverarbeitung. In: Duwe I., Kurfess F., Paass G., Vogel S. (Eds.) Herbstschule Konnektionismus und Neuronale Netze. GMD, Sankt Augustin, 1994.

 

Wermter, S. Evaluating Hybrid and Connectionist Models for Representing Sequentiality in Language, VM-Memo 6, University of Hamburg, Hamburg, FRG, 1994.

 

Wermter, S., Lehnert W. G. A Parallel Model for Compositional Similarity of Natural Language Concepts. In: Hahn U., Adriaens G. (Eds.) Parallel Natural Language Processing, pp. 376-394, Ablex Publishers, Norwood, NJ, 1994.

 

Wermter, S., Peters U. Learning Incremental Case Assignments Based on Modular Connectionist Knowledge Sources. Proceedings of the World Congress on Neural Networks, pp. 538-543, San Diego, USA, 1994.

 

Wermter, S. 1993. Konnektionistische/Hybride Verarbeitung Natürlicher Sprache. Künstliche Intelligenz, Vol. 93, No. 1, pp. 42-44.

 

 
Wermter, S. 1993. Connectionist Context Processing for Phrase Filtering. Proceedings of the World Congress on Neural Networks, pp. 100-103, Portland, USA.

 

Wermter, S., Lehnert W. G. 1992. Noun Phrase Analysis with Connectionist Networks. In: Reilly R., Sharkey N. (Eds.) Connectionist Approaches to Language Processing, pp. 75-95, Lawrence Erlbaum Associates, Hillsdale, NJ.

 

 
Wermter, S. 1992. SCANing Understanding: A Hybrid and Connectionist Architecture. Proceedings of the AAAI Workshop on Integrating Neural and Symbolic Processes, pp. 83-90, San Jose, USA.

 

 
Wermter, S. 1992. Learning a Scanning Understanding for "Real-world" Library Categorization. Proceedings of the Conference on Applied Natural Language Processing, pp. 251-252, Trento, Italy.

 

 
Wermter, S. 1992. A Hybrid and Connectionist Architecture for a SCANning Understanding. In: Neumann, B. (Eds.) Proceedings of the 10th European Conference on Artificial Intelligence, pp. 188-192, Vienna, Austria.

 

Wermter, S. 1991. Learning to Classify Natural Language Titles in a Recurrent Connectionist Model. Proceedings of the International Conference on Artificial Neural Networks, Part II, pp. 1715-1718, Espoo, Finland.

 

 
Wermter, S. 1991. Learning the Work of a Librarian: a Connectionist Model for Semantic Classification. Proceedings of the AAAI Spring Symposium on Connectionist Natural Language Processing, pp. 72-77, Stanford, USA.

 

 
Wermter, S. 1991. Learning and Representing Natural Language Phrases in a Hybrid Symbolic/Connectionist Approach. Proceedings of the AAAI Spring Symposium on Machine Learning of Natural Language and Ontology, pp. 191-195, Stanford, CA, USA.

 

 
Wermter, S., Lehnert, W.G. 1990. A Survey of Question Answering in Natural Language Processing. In: Zwaan R. A., Meutsch D. (Eds.) Computer Models and Technology in Media Research, North Holland, Amsterdam.

 

 
Wermter, S. 1990. Combining Symbolic and Connectionist Techniques for Coordination in Natural Language. Marburger H. (Ed.). Proceedings of the 14th German Workshop on Artificial Intelligence, pp. 186-195, Schloss Eringerfeld, FRG.

 

 
Wermter, S., Lehnert W. G. A Hybrid Symbolic/Connectionist Model for Noun Phrase Understanding. Connection Science, Vol. 1 No. 3, pp. 255-272. 1989.

 

 
Wermter, S. 1989. Learning Semantic Relationships in Compound Nouns with Connectionist Networks. Proceedings of the Eleventh Conference of the Cognitive Science Society, pp. 964-971, Ann Arbor, MI, USA.

 

Wermter, S. 1989. Integration of Semantic and Syntactic Constraints for Structural Noun Phrase Disambiguation. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, pp. 1486-1491, Detroit, USA.