Complex local features as determinants of pattern discrimination
نویسندگان
چکیده
منابع مشابه
Pattern Recognition with Local Invariant Features
Local invariant features have shown to be very successful for recognition. They are robust to occlusion and clutter, distinctive as well as invariant to image transformations. In this chapter recent progress on local invariant features is summarized. It is explained how to extract scale and affine-invariant regions and how to obtain discriminant descriptors for these regions. It is then demonst...
متن کاملEarly - Visual Features as Determinants of PerceivedTexture
This thesis is about the perception of texture similarity and the procedures underlying its computation. A model of texture similarity was engineered using a collection of simulated early-visual operations. These operations include oriented, multi-scale linear ltering; rectifying non-linearity; divisive normalization; low-order stochastic modeling; recursive cascading; and whitening. The rst ai...
متن کاملDiscrimination of compound gratings: Spatial-frequency channels or local features?
Models based on spatial-frequency channels and local features provide alternative explanations for suprathreshold pattern discrimination. We compared psychophysical discrimination data with the predictions of the Wilson and Gelb channel model and three local-feature models. The features were peak-valley local contrast, peak-peak local contrast, and luminance gradients. We measured visual sensit...
متن کاملComplex Codon Usage Pattern and Compositional Features of Retroviruses
Retroviruses infect a wide range of organisms including humans. Among them, HIV-1, which causes AIDS, has now become a major threat for world health. Some of these viruses are also potential gene transfer vectors. In this study, the patterns of synonymous codon usage in retroviruses have been studied through multivariate statistical methods on ORFs sequences from the available 56 retroviruses. ...
متن کاملExploring Cortical Folding Pattern Variability Using Local Image Features
The variability in cortical morphology across subjects makes it difficult to develop a general atlas of cortical sulci. In this paper, we present a data-driven technique for automatically learning cortical folding patterns from MR brain images. A local image feature-based model is learned using machine learning techniques, to describe brain images as a collection of independent, co-occurring, d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bulletin of the Psychonomic Society
سال: 1986
ISSN: 0090-5054
DOI: 10.3758/bf03330498