| 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 | 253* | 2018 |
| 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 | 139* | 2016 |
| An image-computable psychophysical spatial vision model HH Schütt, FA Wichmann Journal of vision 17 (12), 12-12, 2017 | 23 | 2017 |
| Temporal evolution of the central fixation bias in scene viewing LOM Rothkegel, HA Trukenbrod, HH Schütt, FA Wichmann, R Engbert Journal of Vision 17 (13), 3-3, 2017 | 18 | 2017 |
| Likelihood-based parameter estimation and comparison of dynamical cognitive models. HH Schuett, LOM Rothkegel, HA Trukenbrod, S Reich, FA Wichmann, ... Psychological Review 124 (4), 505, 2017 | 18 | 2017 |
| Influence of initial fixation position in scene viewing LOM Rothkegel, HA Trukenbrod, HH Schütt, FA Wichmann, R Engbert Vision research 129, 33-49, 2016 | 13 | 2016 |
| Disentangling bottom-up versus top-down and low-level versus high-level influences on eye movements over time HH Schütt, LOM Rothkegel, HA Trukenbrod, R Engbert, FA Wichmann Journal of vision 19 (3), 1-1, 2019 | 11 | 2019 |
| Searchers adjust their eye-movement dynamics to target characteristics in natural scenes LOM Rothkegel, HH Schütt, HA Trukenbrod, FA Wichmann, R Engbert Scientific reports 9 (1), 1-12, 2019 | 7 | 2019 |
| Methods and measurements to compare men against machines FA Wichmann, DHJ Janssen, R Geirhos, G Aguilar, HH Schütt, ... Electronic Imaging 2017 (14), 36-45, 2017 | 7 | 2017 |
| Perception of light source distance from shading patterns HH Schütt, F Baier, RW Fleming Journal of Vision 16 (3), 9-9, 2016 | 5 | 2016 |
| Comparing representational geometries using the unbiased distance correlation J Diedrichsen, E Berlot, M Mur, HH Schütt, N Kriegeskorte arXiv preprint arXiv:2007.02789, 2020 | 1 | 2020 |
| Of human observers and deep neural networks: A detailed psychophysical comparison R Geirhos, D Janssen, H Schütt, M Bethge, F Wichmann Journal of Vision 17 (10), 806-806, 2017 | 1 | 2017 |
| A divisive model of midget and parasol ganglion cells explains the contrast sensitivity function HH Schütt, FA Wichmann Journal of Vision 19 (10), 79a-79a, 2019 | | 2019 |
| Color Constancy in Deep Neural Networks AC Flachot, HH Schuett, RW Fleming, F Wichmann, KR Gegenfurtner Journal of Vision 19 (10), 298-298, 2019 | | 2019 |
| Modelling Early Influences on Visual Perception F Wichmann, H Schuett PERCEPTION 48, 8-8, 2019 | | 2019 |
| Predicting fixation densities over time from early visual processing H Schütt, L Rothkegel, H Trukenbrod, R Engbert, F Wichmann Journal of Vision 18 (10), 1210-1210, 2018 | | 2018 |
| Corrections to: An image-computable psychophysical spatial HH Schütt, FA Wichmann | | 2018 |
| Predicting the fixation density over time HH Schütt, LOM Rothkegel, HA Trukenbrod, R Engbert, FA Wichmann | | 2018 |
| We know what we can see-peripheral visibility of search targets shapes eye movement behavior in natural scenes L Rothkegel, H Schütt, H Trukenbrod, F Wichmann, R Engbert Journal of Vision 17 (10), 1120-1120, 2017 | | 2017 |
| Some observations on the psychophysics of Deep Neural Networks D Janssen, H Schuett, F Wichmann Journal of Vision 16 (12), 963-963, 2016 | | 2016 |
Ralf EngbertExperimental and Biological Psychology, University of Potsdam, GermanyVerified email at uni-potsdam.de
