Felix Wichmann
Title
Cited by
Cited by
Year
The psychometric function: I. Fitting, sampling, and goodness of fit
FA Wichmann, NJ Hill
Perception & psychophysics 63 (8), 1293-1313, 2001
21972001
The psychometric function: II. Bootstrap-based confidence intervals and sampling
FA Wichmann, NJ Hill
Perception & psychophysics 63 (8), 1314-1329, 2001
8672001
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
R Geirhos, P Rubisch, C Michaelis, M Bethge, FA Wichmann, W Brendel
arXiv preprint arXiv:1811.12231, 2018
4122018
The contributions of color to recognition memory for natural scenes.
FA Wichmann, LT Sharpe, KR Gegenfurtner
Journal of Experimental Psychology: Learning, Memory, and Cognition 28 (3), 509, 2002
2852002
A nonparametric approach to bottom-up visual saliency
W Kienzle, FA Wichmann, MO Franz, B Schölkopf
Advances in neural information processing systems, 689-696, 2007
2572007
Inference for psychometric functions in the presence of nonstationary behavior
I Fründ, NV Haenel, FA Wichmann
Journal of vision 11 (6), 16-16, 2011
2362011
Center-surround patterns emerge as optimal predictors for human saccade targets
W Kienzle, MO Franz, B Schölkopf, FA Wichmann
Journal of vision 9 (5), 7-7, 2009
1742009
Bayesian inference for psychometric functions
M Kuss, F Jäkel, FA Wichmann
Journal of Vision 5 (5), 8-8, 2005
1442005
Spatial four-alternative forced-choice method is the preferred psychophysical method for naïve observers
F Jäkel, FA Wichmann
Journal of Vision 6 (11), 13-13, 2006
1312006
Generalisation in humans and deep neural networks
R Geirhos, CRM Temme, J Rauber, HH Schütt, M Bethge, FA Wichmann
Advances in neural information processing systems, 7538-7550, 2018
1192018
Quantifying the effect of intertrial dependence on perceptual decisions
I Fründ, FA Wichmann, JH Macke
Journal of vision 14 (7), 9-9, 2014
1192014
Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data
HH Schütt, S Harmeling, JH Macke, FA Wichmann
Vision Research 122, 105-123, 2016
1152016
Comparing deep neural networks against humans: object recognition when the signal gets weaker
R Geirhos, DHJ Janssen, HH Schütt, J Rauber, M Bethge, FA Wichmann
arXiv preprint arXiv:1706.06969, 2017
1092017
Texture and haptic cues in slant discrimination: reliability-based cue weighting without statistically optimal cue combination
P Rosas, J Wagemans, MO Ernst, FA Wichmann
JOSA A 22 (5), 801-809, 2005
1092005
Animal detection in natural scenes: critical features revisited
FA Wichmann, J Drewes, P Rosas, KR Gegenfurtner
Journal of Vision 10 (4), 6-6, 2010
982010
Phase noise and the classification of natural images
FA Wichmann, DI Braun, KR Gegenfurtner
Vision research 46 (8-9), 1520-1529, 2006
982006
Transcranial magnetic stimulation in the visual system. I. The psychophysics of visual suppression
T Kammer, K Puls, H Strasburger, NJ Hill, FA Wichmann
Experimental brain research 160 (1), 118-128, 2005
962005
Gender classification of human faces
ABA Graf, FA Wichmann
International Workshop on Biologically Motivated Computer Vision, 491-500, 2002
892002
Spatial statistics and attentional dynamics in scene viewing
R Engbert, HA Trukenbrod, S Barthelmé, FA Wichmann
Journal of vision 15 (1), 14-14, 2015
752015
How to find interesting locations in video: a spatiotemporal interest point detector learned from human eye movements
W Kienzle, B Schölkopf, FA Wichmann, MO Franz
Joint Pattern Recognition Symposium, 405-414, 2007
702007
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Articles 1–20