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8 results (View BibTeX file of all listed publications)

1998

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Masking by plaid patterns: effects of presentation time and mask contrast

Wichmann, F., Henning, G.

pages: 115, 1. T{\"u}binger Wahrnehmungskonferenz (TWK 98), February 1998 (poster)

Abstract
Most current models of early spatial vision comprise of sets of orientation- and spatial-frequency selective filters with our without limited non-linear interactions amongst different subsets of the filters. The performance of human observers and of such models for human spatial vision were compared in experiments using maskers with two spatial frequencies (plaid masks). The detectability of horizontally orientated sinusoidal signals at 3.02 c/deg was measured in standard 2AFC-tasks in the presence of plaid patterns with two-components at the same spatial frequency as the signal but at different orientations (+/- 15, 30, 45, and 75 deg from the signal) and with varying contrasts (1.0, 6.25 and 25.0% contrast). In addition, the temporal envelope of the stimulus presentation was either a rectangular pulse of 19.7 msec duration, or a temporal Hanning window of 1497 msec.Threshold elevation varied with plaid component orientation, peaked +/- 30 deg from the signal where nearly a log unit threshold elevation for the 25.0% contrast plaid was observed. For plaids with 1.0% contrast we observed significant facilitation even with plaids whose components were 75 deg from that of the signal. Elevation factors were somewhat lower for the short stimulus presentation time but were still significant (up to a factor of 5 or 6). Despite of the simple nature of the stimuli employed in this study-sinusoidal signal and plaid masks comprised of only two sinusoids-none of the current models of early spatial vision can fully account for all the data gathered.

Web [BibTex]

1998

Wichmann, F., Henning, G. Masking by plaid patterns: effects of presentation time and mask contrast pages: 115, 1. T{\"u}binger Wahrnehmungskonferenz (TWK 98), February 1998 (poster)

Web [BibTex]

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Generalization bounds and learning rates for Regularized principal manifolds

Smola, A., Williamson, R., Schölkopf, B.

NeuroCOLT, 1998, NeuroColt2-TR 1998-027 (techreport)

[BibTex]

Smola, A., Williamson, R., Schölkopf, B. Generalization bounds and learning rates for Regularized principal manifolds NeuroCOLT, 1998, NeuroColt2-TR 1998-027 (techreport)

[BibTex]

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Generalization Bounds for Convex Combinations of Kernel Functions

Smola, A., Williamson, R., Schölkopf, B.

Royal Holloway College, 1998 (techreport)

[BibTex]

Smola, A., Williamson, R., Schölkopf, B. Generalization Bounds for Convex Combinations of Kernel Functions Royal Holloway College, 1998 (techreport)

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Generalization Performance of Regularization Networks and Support Vector Machines via Entropy Numbers of Compact Operators

Williamson, R., Smola, A., Schölkopf, B.

(19), NeuroCOLT, 1998, Accepted for publication in IEEE Transactions on Information Theory (techreport)

[BibTex]

Williamson, R., Smola, A., Schölkopf, B. Generalization Performance of Regularization Networks and Support Vector Machines via Entropy Numbers of Compact Operators (19), NeuroCOLT, 1998, Accepted for publication in IEEE Transactions on Information Theory (techreport)

[BibTex]

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A bootstrap method for testing hypotheses concerning psychometric functions

Hill, N., Wichmann, F.

1998 (poster)

Abstract
Whenever psychometric functions are used to evaluate human performance on some task, it is valuable to examine not only the threshold and slope values estimated from the original data, but also the expected variability in those measures. This allows psychometric functions obtained in two experimental conditions to be compared statistically. We present a method for estimating the variability of thresholds and slopes of psychometric functions. This involves a maximum-likelihood fit to the data using a three-parameter mathematical function, followed by Monte Carlo simulation using the first fit as a generating function for the simulations. The variability of the function's parameters can then be estimated (as shown by Maloney, 1990), as can the variability of the threshold value (Foster & Bischof, 1997). We will show how a simple development of this procedure can be used to test the significance of differences between (a) the thresholds, and (b) the slopes of two psychometric functions. Further, our method can be used to assess the assumptions underlying the original fit, by examining how goodness-of-fit differs in simulation from its original value. In this way data sets can be identified as being either too noisy to be generated by a binomial observer, or significantly "too good to be true." All software is written in MATLAB and is therefore compatible across platforms, with the option of accelerating performance using MATLAB's plug-in binaries, or "MEX" files.

[BibTex]

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Quantization Functionals and Regularized PrincipalManifolds

Smola, A., Mika, S., Schölkopf, B.

NeuroCOLT, 1998, NC2-TR-1998-028 (techreport)

[BibTex]

Smola, A., Mika, S., Schölkopf, B. Quantization Functionals and Regularized PrincipalManifolds NeuroCOLT, 1998, NC2-TR-1998-028 (techreport)

[BibTex]

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Nonlinearities and the pedestal effect

Wichmann, F., Henning, G., Ploghaus, A.

Perception, 27, pages: S86, 1998 (poster)

Abstract
Psychophysical and physiological evidence suggests that luminance patterns are independently analysed in "channels" responding to different bands of spatial frequency. There are, however, interactions among stimuli falling well outside the usual estimates of channels' bandwidths (Henning, Hertz, and Broadbent, (1975). Vision Res., 15, 887-899). We examined whether the masking results of Henning et al. are consistent with independent channels. We postulated, before the channels, a point non-linearity which would introduce distortion products that might produce the observed interactions between stimuli two octaves apart in spatial frequency. Standard 2-AFC masking experiments determined whether possible distortion products of a 4.185 c/deg masking sinusoid revealed their presence through effects on the detection of a sinusoidal signal at the frequency of the second harmonic of the masker-8.37 c/deg. The signal and masker were horizontally orientated and the signal was in-phase, out-of-phase, or in quadrature with the putative second-order distortion product of the masker. Significant interactions between signal and masker were observed: for a wide range of masker contrasts, signal detection was facilitated by the masking stimulus. However, the shapes of the functions relating detection performance to masker contrast, as well as the effects of relative phase, were inconsistent with the notion that distortion products were responsible for the interactions observed.

[BibTex]

Wichmann, F., Henning, G., Ploghaus, A. Nonlinearities and the pedestal effect Perception, 27, pages: S86, 1998 (poster)

[BibTex]

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Support Vector Machine Reference Manual

Saunders, C., Stitson, M., Weston, J., Bottou, L., Schölkopf, B., Smola, A.

(CSD-TR-98-03), Department of Computer Science, Royal Holloway, University of London, 1998 (techreport)

PostScript [BibTex]

Saunders, C., Stitson, M., Weston, J., Bottou, L., Schölkopf, B., Smola, A. Support Vector Machine Reference Manual (CSD-TR-98-03), Department of Computer Science, Royal Holloway, University of London, 1998 (techreport)

PostScript [BibTex]