Computational models of visual processing - download pdf or read online

By Michael Landy, J. Anthony Movshon

ISBN-10: 0262121557

ISBN-13: 9780262121552

The plenoptic functionality and the weather of early imaginative and prescient / Edward H. Adelson and James R. Bergen --
Learning receptor positions / Albert J. Ahumada, Jr. --
A version of aliasing in extrafoveal human imaginative and prescient / Carlo L.M. Tiana ... [et al.] --
Models of human rod receptors and the ERG / Donald C. Hood and David G. Birch --
The layout of chromatically opponent receptive fields / Peter Lennie, P. William Haake, and David R. Williams --
Spatial receptive box association in monkey V1 and its courting to the cone mosaic / Michael J. Hawken and Andrew J. Parker --
Neural distinction sensitivity / Andrew B. Watson --
Spatiotemporal receptive fields and path selectivity / Robert Shapely, R. Clay Reid, and Robert Soodak --
Nonlinear version of neural responses in cat visible cortex / David J. Heeger. A template matching version of subthreshold summation / Jacob Nachmias --
Noise within the visible approach might be early / Denis G. Pelli --
Pattern discrimination, visible filters, and spatial sampling irregularity / Hugh R. Wilson --
A bilinear version of the illuminant's impression on colour visual appeal / David H. Brainard and Brian A. Wandell --
Shading ambiguity : reflectance and illumination / Michael D'Zmura --
Transparency and the cooperative computation of scene attributes / Daniel Kersten --
Theories for the visible belief of neighborhood speed and coherent movement / Norberto M. Grzywacz and Alan L. Yuille --
Computational modeling of visible texture segregation / James R. Bergen and Michael S. Landy --
Complex channels, early neighborhood nonlinearities, and normalization in texture segregation / Norma Graham. Orthogonal distribution research : a brand new method of the research of texture notion / Charles Chubb and Michael S. Landy --
Shape from X : psychophysics and computation / Heinrichs H. Bülthoff --
Computational matters in fixing the stereo correspondence challenge / John P. Frisby and Stephen B. Pollard --
Stereo, surfaces, and form / Andrew J. Parker ... [et al.].

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C • III Fig. 7 The weight adjustment network of model 2. The dotted lines show the original signal weighting network. Layer A shows the weights, which are multiplied by the input values in layer B and summed at layer C. Layer 1 has a spontaneous unit which has generated the signal in layer 2 (not shown here) that is entering on the input lines (unterminateti) on the far left. Layer 3 sends the error signal back to layer 4, which computes the product of the error and the input. Layer 5 adjusts the gain by the leaming rate.

The correct projective field is formed and is then dragged around to the other positions. When the learning rate is less than unity, the process does not copy from one place 31 The first two models have been previously described by Ahumada and Yellott (1989). That presentation also describes ways of speeding up the convergence of the matrix inversion calculation, while still maintaining one computational advantage of the method described here. its ability to take advantage of locality in the spread functions.

The observer was shown either a vertical or a horizontal stationary interference fringe on each trial and was asked In this range of frequencies, percent correct on the mo­ to identify its orientation. There is a range of spatial tion discrimination task fell reliably below chance perfor­ frequencies in which observers reliably report the wrong mance. At a still higher frequency, the direction of motion orientation for the stimulus presented. enlation rr:�ersal • molion 50 .... .... . o 10 , " " re"frsal .........

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Computational models of visual processing by Michael Landy, J. Anthony Movshon


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