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Erhardt Barth

Showing results (1-10 of 16) with videos related to

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Visual Cognition|July 31, 2012
Eye movement prediction and variability on natural video data setsMichael Dorr, Eleonora Vig, Erhardt Barth
Frontiers in Psychology|June 8, 2017
Using CNN Features to Better Understand What Makes Visual Artworks SpecialAnselm Brachmann, Erhardt Barth, Christoph Redies
Spatial Vision|October 10, 2009
Efficient visual coding and the predictability of eye movements on natural moviesEleonora Vig, Michael Dorr, Erhardt Barth
Journal of Vision|January 13, 2022
FP-nets as novel deep networks inspired by visionPhilipp Grüning, Thomas Martinetz, Erhardt Barth
IEEE Transactions on Neural Networks|November 13, 2008
Simple method for high-performance digit recognition based on sparse codingKai Labusch, Erhardt Barth, Thomas Martinetz
Vision Research|September 22, 2009
The contribution of low-level features at the centre of gaze to saccade target selectionMichael Dorr, Karl R Gegenfurtner, Erhardt Barth
Sensors (Basel, Switzerland)|September 27, 2019
Ensembles of Deep Learning Models and Transfer Learning for Ear RecognitionHammam Alshazly, Christoph Linse, Erhardt Barth, et al.
Sensors (Basel, Switzerland)|January 14, 2021
Explainable COVID-19 Detection Using Chest CT Scans and Deep LearningHammam Alshazly, Christoph Linse, Erhardt Barth, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|April 21, 2012
Intrinsic dimensionality predicts the saliency of natural dynamic scenesEleonora Vig, Michael Dorr, Thomas Martinetz, et al.
Journal of Vision|October 2, 2010
Variability of eye movements when viewing dynamic natural scenesMichael Dorr, Thomas Martinetz, Karl R Gegenfurtner, et al.
Pageof 2

Showing results (1-10 of 16) with videos related to

Sort By:
Pageof 2
Visual Cognition|July 31, 2012
Eye movement prediction and variability on natural video data setsMichael Dorr, Eleonora Vig, Erhardt Barth
Frontiers in Psychology|June 8, 2017
Using CNN Features to Better Understand What Makes Visual Artworks SpecialAnselm Brachmann, Erhardt Barth, Christoph Redies
Spatial Vision|October 10, 2009
Efficient visual coding and the predictability of eye movements on natural moviesEleonora Vig, Michael Dorr, Erhardt Barth
Journal of Vision|January 13, 2022
FP-nets as novel deep networks inspired by visionPhilipp Grüning, Thomas Martinetz, Erhardt Barth
IEEE Transactions on Neural Networks|November 13, 2008
Simple method for high-performance digit recognition based on sparse codingKai Labusch, Erhardt Barth, Thomas Martinetz
Vision Research|September 22, 2009
The contribution of low-level features at the centre of gaze to saccade target selectionMichael Dorr, Karl R Gegenfurtner, Erhardt Barth
Sensors (Basel, Switzerland)|September 27, 2019
Ensembles of Deep Learning Models and Transfer Learning for Ear RecognitionHammam Alshazly, Christoph Linse, Erhardt Barth, et al.
Sensors (Basel, Switzerland)|January 14, 2021
Explainable COVID-19 Detection Using Chest CT Scans and Deep LearningHammam Alshazly, Christoph Linse, Erhardt Barth, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|April 21, 2012
Intrinsic dimensionality predicts the saliency of natural dynamic scenesEleonora Vig, Michael Dorr, Thomas Martinetz, et al.
Journal of Vision|October 2, 2010
Variability of eye movements when viewing dynamic natural scenesMichael Dorr, Thomas Martinetz, Karl R Gegenfurtner, et al.
Pageof 2