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Literaturliste von D. Phil. Felix A. Wichmann

letzte Aktualisierung: 13.11.2023

Huber, L. S., Geirhos, R. & Wichmann, F. A. (2023). The developmental trajectory of object recognition robustness: Children are like small adults but unlike big deep neural networks. Journal of Vision, 23(7), No. 4.

Flachot, A., Akbarinia, A., Schütt, H. H., Fleming, R. W., Wichmann, F. A. & Gegenfurtner, K. R. (2022). Deep neural models for color classification and color constancy. Journal of Vision, 22(4), No. 17.

Meding, K., Bruijns, S. A., Schölkopf, B., Berens, P. & Wichmann, F. A. (2020). Phenomenal causality and sensory realism. i-Perception, 11(3), 1-16.

Rothkegel, L. O. M., Schütt, H. H., Trukenbrod, H. A., Wichmann, F. A. & Engbert, R. (2019). Searchers adjust their eye-movement dynamics to target characteristics in natural scenes. Scientific Reports, 9, No. 1635.

Schütt, H. H., Rothkegel, L. O. M., Trukenbrod, H. A., Engbert, R. & Wichmann, F. A. (2019). Disentangling bottom-up versus top-down and low-level versus high-level influences on eye movements over time. Journal of Vision, 19(3), No. 1.

Trukenbrod, H. A., Barthelme, S., Wichmann, F. A. & Engbert, R. (2019). Spatial statistics for gaze patterns in scene viewing: Effects of repeated viewing. Journal of Vision, 19(6), No. 5.

Aguilar, G., Wichmann, F. A. & Maertens, M. (2017). Comparing sensitivity estimates from MLDS and forced-choice methods in a slant-from-texture experiment. Journal of Vision, 17(1), No. 37.

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A. & Engbert, R. (2017). Temporal evolution of the central fixation bias in scene viewing. Journal of Vision, 17(13), No. 3.

Schuett, H. H., Wichmann, F. A., Rothkegel, L. O. M., Trukenbrod, H. A., Engbert, R. & Reich, S. (2017). Likelihood-Based Parameter Estimation and Comparison of Dynamical Cognitive Models. Psychological Review, 124(4), 505-524.

Schütt, H. H. & Wichmann, F. A. (2017). An image-computable psychophysical spatial vision model. Journal of Vision, 17(12), No. 12.

Wallis, T. S. A., Tobias, S., Wichmann, F. A. & Bethge, M. (2017). Detecting distortions of peripherally presented letter stimuli under crowded conditions. Attention, Perception, & Psychophysics, 79(3), 850-862.

Jaekel, F., Singh, M., Wichmann, F. A. & Herzog, M. H. (2016). An overview of quantitative approaches in Gestalt perception. Vision Research, 3-8.

Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A. & Obermayer, K. (2016). BOiS - Berlin object in scene database: Controlled photographic images for visual search experiments with quantified contextual priors. Frontiers in Psychology (Online Journal), 7, No. 749.

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A. & Engbert, R. (2016). Influence of initial fixation position in scene viewing. Vision Research, 129, 33-49.

Schütt, H. H., Harmeling, S., Macke, J. H. & Wichmann, F. A. (2016). Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research, 122, 105-123.

Betz, T., Shapley, R., Wichmann, F. A. & Maertens, M. (2015). Noise masking of White's illusion exposes the weakness of current spatial filtering models of lightness perception. Journal of Vision, 15(14), No. 1, 1-17.

Betz, T., Shapley, R., Wichmann, F. A. & Maertens, M. (2015). Testing the role of luminance edges in White's illusion with contour adaptation. Journal of Vision, 15(11), 14,1-16.

Engbert, R., Trukenbrod, H. A., Barthelmé, S. & Wichmann, F. A. (2015). Spatial statistics and attentional dynamics in scene viewing. Journal of Vision, 15(1), No. 14, 1-17.

Maertens, M., Wichmann, F. A. & Shapley, R. (2015). Context affects lightness at the level of surfaces. Journal of Vision, 15(1), No. 15, 1-15.

Fründ, I., Wichmann, F. A. & Macke, J. H. (2014). Quantifying the effect of intertrial dependence on perceptual decisions. Journal of Vision, 14(7), 1-16.

Barthelmé, S., Trukenbrod, H. A., Engbert, R. & Wichmann, F. A. (2013). Modeling fixation locations using spatial point processes. Journal of Vision, 13(12), 1-34.

Gerhard, H. E., Wichmann, F. A. & Bethge, M. (2013). How sensitive is the human visual system to the local statistics of natural images? PLoS Computational Biology, 9(1).

Goris, R. L. T., Putzeys, T., Wagemans, J. & Wichmann, F. A. (2013). A neural population model for visual pattern detection. Psychological Review, 120(3), 472-496.

Maertens, M. & Wichmann, F. A. (2013). When luminance increment thresholds depend on apparent lightness. Journal of Vision, 13(6), 1-11.

Schönfelder, V. H. & Wichmann, F. A. (2013). Identification of stimulus cues in narrow-band tone-in-noise detection using sparse observer models. Journal of the Acoustical Society of America, 134(1), 447-463.

Putzeys, T., Bethge, M., Wichmann, F., Wagemanns, J. & Goris, R. (2012). A new perceptual bias reveals suboptimal population decoding of sensory responses. PLoS Computational Biology, 8(4), No. e1002453.

Schönfelder, V. H. & Wichmann, F. A. (2012). Sparse regularized regression identifies behaviorally-relevant stimulus features from psychophysical data. Journal of the Acoustical Society of America, 131(5), 3953-3969.

Fründ, I., Haenel, N. V. & Wichmann, F. A. (2011). Inference for psychometric functions in the presence of nonstationary behavior. Journal of Vision, 11(6), 1-19.

Rosas, P. & Wichmann, F. A. (2011). Cue combination: Beyond optimality. In J. Trommershäuser, K. P. Körding & M. S. Landy (Eds.), Sensory cue integration (pp. 144-152). New York: Oxford University Press.

Macke, J. H. & Wichmann, F. A. (2010). Estimating predictive stimulus features from psychophysical data: The decision image technique applied to human faces. Journal of Vision, 10(5), 1-24.

Wichmann, F. A., Drewes, J., Rosas, P. & Gegenfurtner, K. R. (2010). Animal detection in natural scenes: Critical features revisited. Journal of Vision, 10.

Goris, R. L. T., Wichmann, F. A. & Henning, G. B. (2009). A neurophysiologically plausible population code model for human contrast discrimination. Journal of Vision, 9(7), 755-777.

Jäkel, F., Schölkopf, B. & Wichmann, F. A. (2009). Does cognitive science need kernels? Trends in Cognitive Sciences, 13(9), 381-388.

Kienzle, W., Franz, M. O., Schölkopf, B. & Wichmann, F. A. (2009). Center-surround patterns emerge as optimal predictors for human saccade targets. Journal of Vision, 9(5), 1-15.

Thielscher, A. & Wichmann, F. A. (2009). Determining the cortical target of transcranial magnetic stimulation. NeuroImage, 47(4), 1319-1330.

Goris, R. L. T., Wagemans, J. & Wichmann, F. A. (2008). Modelling contrast discrimination data suggest both the pedestal effect and stochastic resonance to be caused by the same mechanism. Journal of Vision, 8(15), 1-21.

Jäkel, F., Schölkopf, B. & Wichmann, F. A. (2008). Generalization and similarity in exemplar models of categorization: Insights from machine learning. Psychonomic Bulletin & Review, 15(2), 256-271.

Jäkel, F., Schölkopf, B. & Wichmann, F. A. (2008). Similarity, kernels, and the triangle inequality. Journal of Mathematical Psychology, 52(5), 297-303.

Henning, G. B. & Wichmann, F. A. (2007). Some observations on the pedestal effect. Journal of Vision, 7(1), 3, 1-15.

Jäkel, F., Schölkopf, B. & Wichmann, F. A. (2007). A tutorial on kernel methods for categorization. Journal of Mathematical Psychology, 51(6), 343-358.

Kienzle, W., Wichmann, F. A., Schölkopf, B. & Franz, M. O. (2007). A nonparametric approach to bottom-up visual saliency. In B. Schölkopf, J. Platt & T. Hoffman (Eds.), Advances in neural information processing systems 19. Proceedings of the 2006 conference (pp. 689-696). Cambridge: MIT Press.

Laub, J., Macke, J., Müller, K.-R. & Wichmann, F. (2007). Inducing metric violations in human similarity judgements. In B. Schölkopf, J. Platt & T. Hoffman (Eds.), Advances in neural information processing systems 19. Proceedings of the 2006 conference (pp. 777-784). Cambridge, MA: MIT Press.

Rosas, P., Wichmann, F. A. & Wagemans, J. (2007). Texture and object motion in slant discrimination: Failure of reliability-based weighting of cues may be evidence for strong fusion. Journal of Vision, 7(6), 1-21.

Graf, A. B. A., Wichmann, F. A., Bülthoff, H. H. & Schölkopf, B. (2006). Classification of faces in man and machine. Neural Computation, 18(1), 143-165.

Jäkel, F. & Wichmann, F. A. (2006). Spatial four-alternative forced-choice method is the preferred psychophysical method for naïve observers. Journal of Vision, 6(11), 1307-1322.

Wichmann, F. A., Braun, D. I. & Gegenfurtner, K. R. (2006). Phase noise and the classification of natural images. Vision Research, 46(8-9), 1520-1529.

Kammer, T., Puls, K., Strasburger, H., Hill, N. J. & Wichmann, F. A. (2005). Transcranial magnetic stimulation in the visual system. I. The psychophysics of visual suppression. Experimental Brain Research, 160(1), 118-128.

Kuss, M., Jäkel, F. & Wichmann, F. A. (2005). Bayesian inference for psychometric functions. Journal of Vision, 5(5), 478-492.

Rosas, P., Wagemans, J., Ernst, M. O. & Wichmann, F. A. (2005). Texture and haptic cues in slant discrimination: Reliability-based cue weighting without statistically optimal cue combination. Journal of the Optical Society of America A, 22(5), 801-809.

Wagemans, J., Wichmann, F. A. & Op de Beeck, H. (2005). Visual perception I: Basic principles. In K. Lamberts & R. L. Goldstone (Eds.), Handbook of cognition (pp. 3-47). London: Sage Publications.

Wichmann, F. A., Graf, A. B. A., Simoncelli, E. P., Bülthoff, H. H. & Schölkopf, B. (2005). Machine learning applied to perception: Decision-images for gender classification. In L. K. Saul, Y. Weiss & L. Bottou (Eds.), Advances in neural information processing systems 17. Proceedings of the 2004 conference (pp. 1489-1496). Cambridge: MIT Press.

Graf, A. B. A. & Wichmann, F. A. (2004). Insights from machine learning applied to human visual classification. In S. Thrun, L. K. Saul & B. Schölkopf (Eds.), Advances in neural information processing systems 16. Proceedings of the 2003 conference (pp. 905-912). Cambridge: MIT Press.

Rosas, P., Wichmann, F. A. & Wagemans, J. (2004). Some observations on the effects of slant and texture type on slant-from-texture. Vision Research, 44(13), 1511-1535.

Bird, C. M., Henning, G. B. & Wichmann, F. A. (2002). Contrast discrimination with sinusoidal gratings of different spatial frequency. Journal of the Optical Society of America A, 19(7), 1267-1273.

Graf, A. B. A. & Wichmann, F. A. (2002). Gender classification of human faces. In H. H. Bülthoff, S.-W. Lee, T. A. Poggio & C. Wallraven (Eds.), Biologically motivated computer vision. Second International Workshop, BMCV 2002 Tübingen, Germany, November 22-24, 2002 Proceedings (pp. 491-500). Berlin: Springer Verlag.

Henning, G. B., Bird, C. M. & Wichmann, F. A. (2002). Contrast discrimination with pulse trains in pink noise. Journal of the Optical Society of America A, 19(7), 1259-1266.

Wichmann, F. A., Sharpe, L. T. & Gegenfurtner, K. R. (2002). The contributions of color to recognition memory for natural scenes. Journal of Experimental Psychology - Learning, Memory, and Cognition, 28(3), 509-520.

Wichmann, F. A. & Hill, N. J. (2001). The psychometric function: I. Fitting, sampling and goodness of fit. Perception and Psychophysics, 63(8), 1293-1313.

Wichmann, F. A. & Hill, N. J. (2001). The psychometric function: II. Bootstrap-based confidence intervals and sampling. Perception and Psychophysics, 63(8), 1314-1329.

Gegenfurtner, K. R., Wichmann, F. A. & Sharpe, L. T. (1998). The contribution of color to visual memory in X-chromosome-linked dichromats. Vision Research, 38(7), 1041-1045.

Wichmann, F. A. & Henning, G. B. (1998). No role for motion blur in either motion detection or motion-based image segmentation. Journal of the Optical Society of America A, 15(2), 297-306.



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