Tobias Brosch
Tobias Brosch
Institute of Neural Information Processing, University of Ulm, Germany
Verified email at uni-ulm.de
Title
Cited by
Cited by
Year
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
1142011
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
502012
On Event-Based Optical Flow Detection
T Brosch, S Tschechne, H Neumann
Frontiers in Neuroscience 9 (137), 1-15, 2015
452015
Computing with a Canonical Neural Circuits Model with Pool Normalization and Modulating Feedback
T Brosch, H Neumann
Neural Computation 26 (12), 2735-89, 2014
372014
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
292014
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
262015
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
252013
Event-Based Optical Flow on Neuromorphic Hardware
T Brosch, H Neumann
BICT, 2015
15*2015
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
15*2014
The Brain’s Sequential Parallelism: Perceptual Decision-Making and Early Sensory Responses
T Brosch, H Neumann
LNCS, 41-50, 2012
72012
The Combination of HMAX and HOGs in an Attention Guided Framework for Object Localization
T Brosch, H Neumann
ICPRAM, 281-288, 2012
42012
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
32013
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
22011
Towards a Mesoscopic-Level Canonical Circuit Definition for Visual Cortical Processing
G Layher, T Brosch, H Neumann
BICT, 2015
12015
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
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Articles 1–16