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Visual Cognition
|
July 31, 2012
Eye movement prediction and variability on natural video data sets
Michael Dorr, Eleonora Vig, Erhardt Barth
Frontiers in Psychology
|
June 8, 2017
Using CNN Features to Better Understand What Makes Visual Artworks Special
Anselm Brachmann, Erhardt Barth, Christoph Redies
Spatial Vision
|
October 10, 2009
Efficient visual coding and the predictability of eye movements on natural movies
Eleonora Vig, Michael Dorr, Erhardt Barth
Journal of Vision
|
January 13, 2022
FP-nets as novel deep networks inspired by vision
Philipp Grüning, Thomas Martinetz, Erhardt Barth
IEEE Transactions on Neural Networks
|
November 13, 2008
Simple method for high-performance digit recognition based on sparse coding
Kai Labusch, Erhardt Barth, Thomas Martinetz
Vision Research
|
September 22, 2009
The contribution of low-level features at the centre of gaze to saccade target selection
Michael Dorr, Karl R Gegenfurtner, Erhardt Barth
Sensors (Basel, Switzerland)
|
September 27, 2019
Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition
Hammam Alshazly, Christoph Linse, Erhardt Barth, et al.
Sensors (Basel, Switzerland)
|
January 14, 2021
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
Hammam 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 scenes
Eleonora Vig, Michael Dorr, Thomas Martinetz, et al.
Journal of Vision
|
October 2, 2010
Variability of eye movements when viewing dynamic natural scenes
Michael Dorr, Thomas Martinetz, Karl R Gegenfurtner, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 16) with videos related to
Sort By:
Page
of 2
Visual Cognition
|
July 31, 2012
Eye movement prediction and variability on natural video data sets
Michael Dorr, Eleonora Vig, Erhardt Barth
Frontiers in Psychology
|
June 8, 2017
Using CNN Features to Better Understand What Makes Visual Artworks Special
Anselm Brachmann, Erhardt Barth, Christoph Redies
Spatial Vision
|
October 10, 2009
Efficient visual coding and the predictability of eye movements on natural movies
Eleonora Vig, Michael Dorr, Erhardt Barth
Journal of Vision
|
January 13, 2022
FP-nets as novel deep networks inspired by vision
Philipp Grüning, Thomas Martinetz, Erhardt Barth
IEEE Transactions on Neural Networks
|
November 13, 2008
Simple method for high-performance digit recognition based on sparse coding
Kai Labusch, Erhardt Barth, Thomas Martinetz
Vision Research
|
September 22, 2009
The contribution of low-level features at the centre of gaze to saccade target selection
Michael Dorr, Karl R Gegenfurtner, Erhardt Barth
Sensors (Basel, Switzerland)
|
September 27, 2019
Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition
Hammam Alshazly, Christoph Linse, Erhardt Barth, et al.
Sensors (Basel, Switzerland)
|
January 14, 2021
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
Hammam 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 scenes
Eleonora Vig, Michael Dorr, Thomas Martinetz, et al.
Journal of Vision
|
October 2, 2010
Variability of eye movements when viewing dynamic natural scenes
Michael Dorr, Thomas Martinetz, Karl R Gegenfurtner, et al.
Page
of 2