| Multiple classifier systems for the classification of audio-visual emotional states M Glodek, S Tschechne, G Layher, M Schels, T Brosch, S Scherer, ... Affective Computing and Intelligent Interaction, 359-368, 2011 | 124 | 2011 |
| A generic framework for the inference of user states in human computer interaction S Scherer, M Glodek, G Layher, M Schels, M Schmidt, T Brosch, ... Journal on Multimodal User Interfaces 6 (3-4), 117-141, 2012 | 52 | 2012 |
| On Event-Based Optical Flow Detection T Brosch, S Tschechne, H Neumann Frontiers in Neuroscience 9 (137), 1-15, 2015 | 51 | 2015 |
| Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback T Brosch, H Neumann Neural Computation 26 (12), 2735-89, 2014 | 39 | 2014 |
| Interaction of Feedforward and Feedback Streams in Visual Cortex in a Firing-Rate Model of Columnar Computations H Brosch, T. and Neumann Neural Networks 54, 11-6, 2014 | 30 | 2014 |
| Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks PR Brosch, T. and Neumann, H. and Roelfsema PLoS Computational Biology 11 (10), e1004489, 2015 | 26 | 2015 |
| Multi-modal classifier-fusion for the recognition of emotions M Schels, M Glodek, S Meudt, S Scherer, M Schmidt, G Layher, ... Coverbal Synchrony in Human-Machine Interaction, 73, 2013 | 26 | 2013 |
| On Event-Based Motion Detection and Integration H Tschechne, S. and Brosch, T. and Sailer, R. and von Egloffstein, N. and ... 8th International Conference on Bio-inspired Information and Communications …, 2014 | 17* | 2014 |
| Event-Based Optical Flow on Neuromorphic Hardware T Brosch, H Neumann BICT, 2015 | 15* | 2015 |
| The Brain’s Sequential Parallelism: Perceptual Decision-Making and Early Sensory Responses T Brosch, H Neumann LNCS, 41-50, 2012 | 7 | 2012 |
| Attention-Gated Reinforcement Learning in Neural Networks—A Unified View T Brosch, F Schwenker, H Neumann Artificial Neural Networks and Machine Learning–ICANN 2013 8131, 272-279, 2013 | 4 | 2013 |
| The Combination of HMAX and HOGs in an Attention Guided Framework for Object Localization T Brosch, H Neumann ICPRAM, 281-288, 2012 | 4 | 2012 |
| Social Signal Processing in Companion Systems - Challenges Ahead G Layher, S Tschechne, S Scherer, T Brosch, C Curio, H Neumann GI-Edition LNI 192, 239-53, 2011 | 2 | 2011 |
| Towards a Mesoscopic-Level Canonical Circuit Definition for Visual Cortical Processing G Layher, T Brosch, H Neumann BICT, 2015 | 1 | 2015 |
| Learning of New Perceptual Groupings - A Biologically Plausible Recurrent Neural Network Model that Learns Contour Integration T Brosch, P Roelfsema, H Neumann Journal of Vision (Abstract, VSS) 14 (10), 941, 2014 | | 2014 |
| Perceptual Crowding in a Neural Model of Feedforward-Feedback Interactions T Brosch, H Neumann Journal of Vision 12 (9), 329-329, 2012 | | 2012 |
Heiko NeumannProfessor for Computer Science, Ulm University, Institute of Neural Information ProcessingEmail verificata su uni-ulm.de
