Sven Eberhardt
Sven Eberhardt
Verified email at brown.edu - Homepage
Title
Cited by
Cited by
Year
How deep is the feature analysis underlying rapid visual categorization?
S Eberhardt, JG Cader, T Serre
Advances in neural information processing systems, 1100-1108, 2016
282016
Learning what and where to attend
D Linsley, D Shiebler, S Eberhardt, T Serre
arXiv preprint arXiv:1805.08819, 2018
162018
What are the visual features underlying human versus machine vision?
D Linsley, S Eberhardt, T Sharma, P Gupta, T Serre
Proceedings of the IEEE International Conference on Computer Vision …, 2017
162017
Global-and-local attention networks for visual recognition
D Linsley, D Scheibler, S Eberhardt, T Serre
arXiv preprint arXiv:1805.08819, 2018
102018
Data carrier designed for contactless communication and having detection means for detecting a temperature prevailing in the data carrier
M Cernusca, S Posch, J Preishuber-Pfluegl, P Thueringer
US Patent 6,671,493, 2003
92003
StomataCounter: a neural network for automatic stomata identification and counting
KC Fetter, S Eberhardt, RS Barclay, S Wing, SR Keller
New Phytologist 223 (3), 1671-1681, 2019
72019
Peripheral pooling is tuned to the localization task
S Eberhardt, C Zetzsche, K Schill
Journal of Vision 16 (2), 14-14, 2016
72016
Low-level global features for vision-based localizations.
S Eberhardt, C Zetzsche
KIK@ KI, 5-12, 2013
72013
Local depth edge detection in humans and deep neural networks
KA Ehinger, WJ Adams, EW Graf, JH Elder
Proceedings of the IEEE International Conference on Computer Vision …, 2017
62017
Advances in Neural Information Processing Systems
S Eberhardt, JG Cader, T Serre
52016
From pattern recognition to place identification
S Eberhardt, T Kluth, C Zetzsche, K Schill
Spatial cognition, international workshop on place-related knowledge …, 2012
32012
StomataCounter: a deep learning method applied to automatic stomatal identification and counting
KC Fetter, S Eberhardt, RS Barclay, S Wing, SR Keller
bioRxiv, 327494, 2018
22018
Clicktionary: A Web-based Game for Exploring the Atoms of Object Recognition
D Linsley, S Eberhardt, T Sharma, P Gupta, T Serre
CoRR, 2017
22017
Dynamics of dual prism adaptation: Relating novel experimental results to a minimalistic neural model
O Arévalo, MA Bornschlegl, S Eberhardt, U Ernst, K Pawelzik, M Fahle
PloS one 8 (10), e76601, 2013
22013
Large-scale identification of the visual features used for object recognition with ClickMe. ai
D Linsley, D Shiebler, S Eberhardt, A Karagounis, T Serre
Journal of Vision 18 (10), 414-414, 2018
12018
Analysis and Modeling of Visual Invariance for Object Recognition and Spatial Cognition
S Eberhardt
Universität Bremen, 2015
12015
Method and system for automated behavior classification of test subjects
T Serre, Y Barhomi, Z Nado, K Bath, S Eberhardt
US Patent 10,181,082, 2019
2019
A data-driven approach to learning 3D shape
S Eberhardt, D Schiebler, D Linsley, T Serre
Journal of Vision 17 (10), 405-405, 2017
2017
A novel game for discovering visual features for object recognition.
D Linsley, S Eberhardt, P Gupta, T Serre
Journal of Vision 17 (10), 1249-1249, 2017
2017
Large-scale discovery of visual features for object recognition
D Linsley, S Eberhardt, D Shiebler, T Serre
2017
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