Antonio Rodriguez-Sanchez
Antonio Rodriguez-Sanchez
Senior Researcher, University of Innsbruck
Verified email at uibk.ac.at - Homepage
Title
Cited by
Cited by
Year
Deep hierarchies in the primate visual cortex: What can we learn for computer vision?
N Kruger, P Janssen, S Kalkan, M Lappe, A Leonardis, J Piater, ...
IEEE transactions on pattern analysis and machine intelligence 35 (8), 1847-1871, 2012
3152012
The roles of endstopped and curvature tuned computations in a hierarchical representation of 2D shape
AJ Rodríguez-Sánchez, JK Tsotsos
PLoS One 7 (8), e42058, 2012
592012
The different stages of visual recognition need different attentional binding strategies
JK Tsotsos, AJ Rodríguez-Sánchez, AL Rothenstein, E Simine
Brain research 1225, 119-132, 2008
482008
25 years of cnns: Can we compare to human abstraction capabilities?
S Stabinger, A Rodríguez-Sánchez, J Piater
International Conference on Artificial Neural Networks, 380-387, 2016
432016
A push-pull CORF model of a simple cell with antiphase inhibition improves SNR and contour detection
G Azzopardi, A Rodríguez-Sánchez, J Piater, N Petkov
PLoS One 9 (7), e98424, 2014
402014
Attention and visual search
AJ Rodriguez-Sanchez, E Simine, JK Tsotsos
International Journal of Neural Systems 17 (04), 275-288, 2007
282007
A clash of bottom-up and top-down processes in visual search: The reversed letter effect revisited.
L Zhaoping, U Frith
Journal of Experimental Psychology: Human Perception and Performance 37 (4), 997, 2011
222011
The importance of intermediate representations for the modeling of 2d shape detection: Endstopping and curvature tuned computations
AJ Rodríguez-Sánchez, JK Tsotsos
CVPR 2011, 4321-4326, 2011
222011
Towards affordance detection for robot manipulation using affordance for parts and parts for affordance
SR Lakani, AJ Rodríguez-Sánchez, J Piater
Autonomous Robots 43 (5), 1155-1172, 2019
152019
Training deep capsule networks
D Peer, S Stabinger, A Rodriguez-Sanchez
arXiv preprint arXiv:1812.09707, 2018
15*2018
Different binding strategies for the different stages of visual recognition
JK Tsotsos, AJ Rodriguez-Sanchez, AL Rothenstein, E Simine
International Symposium on Brain, Vision, and Artificial Intelligence, 150-160, 2007
152007
Visual feature binding within the selective tuning attention framework
AL Rothenstein, AJ Rodriguez-Sanchez, E Simine, JK Tsotsos
International Journal of Pattern Recognition and Artificial Intelligence 22 …, 2008
122008
Hierarchical object representations in the visual cortex and computer vision
AJ Rodríguez-Sánchez, M Fallah, A Leonardis
Frontiers in computational neuroscience 9, 142, 2015
102015
SCurV: A 3D descriptor for object classification
AJ Rodríguez-Sánchez, S Szedmak, J Piater
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
92015
Towards sparsity and selectivity: Bayesian learning of restricted Boltzmann machine for early visual features
H Xiong, S Szedmak, A Rodríguez-Sánchez, J Piater
International Conference on Artificial Neural Networks, 419-426, 2014
92014
Limitation of capsule networks
D Peer, S Stabinger, A Rodríguez-Sánchez
Pattern Recognition Letters 144, 68-74, 2021
8*2021
Diversity priors for learning early visual features
H Xiong, AJ Rodríguez-Sánchez, S Szedmak, J Piater
Frontiers in computational neuroscience 9, 104, 2015
82015
A deep learning approach for detecting and correcting highlights in endoscopic images
A Rodríguez-Sánchez, D Chea, G Azzopardi, S Stabinger
2017 seventh international conference on image processing theory, tools and …, 2017
72017
IIS at ImageCLEF 2015: Multi-label classification task
A Rodrıguez-Sánchez, S Fontanella, J Piater, S Szedmak
Working Notes of CLEF 2015, 2015
72015
ISLES challenge: U-shaped convolution neural network with dilated convolution for 3D stroke lesion segmentation
A Tureckova, AJ Rodríguez-Sánchez
International MICCAI Brainlesion Workshop, 319-327, 2018
62018
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Articles 1–20