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ICPR
2004
IEEE
14 years 6 months ago
Large Scale Feature Selection Using Modified Random Mutation Hill Climbing
Feature selection is a critical component of many pattern recognition applications. There are two distinct mechanisms for feature selection, namely the wrapper method and the filt...
Anil K. Jain, Michael E. Farmer, Shweta Bapna
CVPR
2012
IEEE
11 years 7 months ago
Image categorization using Fisher kernels of non-iid image models
The bag-of-words (BoW) model treats images as an unordered set of local regions and represents them by visual word histograms. Implicitly, regions are assumed to be identically an...
Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia...
BMVC
2010
13 years 3 months ago
Generalized RBF feature maps for Efficient Detection
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
PAMI
2002
148views more  PAMI 2002»
13 years 4 months ago
Two Variations on Fisher's Linear Discriminant for Pattern Recognition
Discriminants are often used in pattern recognition to separate clusters of points in some multidimensional "feature" space. This paper provides two fast and simple techn...
Tristrom Cooke
ICCV
2005
IEEE
14 years 7 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona