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» Learning in Computer Vision: Some Thoughts
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ECCV
2004
Springer
14 years 9 months ago
Recognition by Probabilistic Hypothesis Construction
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
Pierre Moreels, Michael Maire, Pietro Perona
ECCV
2010
Springer
14 years 23 days ago
A Fast Dual Method for HIK SVM Learning
Histograms are used in almost every aspect of computer vi-4 4 sion, from visual descriptors to image representations. Histogram Inter-5 5 section Kernel (HIK) and SVM classifiers ...
CVPR
2004
IEEE
14 years 9 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
ICIP
2005
IEEE
14 years 9 months ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
CVPR
2004
IEEE
14 years 9 months ago
Learning Distance Functions for Image Retrieval
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall