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» Abduction in Classification Tasks
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VLSISP
2010
254views more  VLSISP 2010»
14 years 9 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
ICCV
2009
IEEE
16 years 3 months ago
Max-Margin Additive Classifiers for Detection
We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piece-wise linear classifiers, which ...
Subhransu Maji, Alexander C. Berg
CVPR
2008
IEEE
16 years 17 days ago
Looking around the backyard helps to recognize faces and digits
Human beings have the ability to learn to recognize a new visual category based on only one or few training examples. Part of this ability might come from the use of knowledge fro...
Honghao Shan, Garrison W. Cottrell
ICIP
2001
IEEE
16 years 3 days ago
Hyperspectral image coding using 3D transforms
This work considers the efficient coding of hyperspectral images. The shape-adaptive DCT is extended to the three-dimensional case. Both the 3D-SA-DCT and the conventional 3D-DCT ...
Dmitry Markman, David Malah
ICML
2007
IEEE
15 years 11 months ago
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
In this paper we present a novel algorithm, CarpeDiem. It significantly improves on the time complexity of Viterbi algorithm, preserving the optimality of the result. This fact ha...
Roberto Esposito, Daniele P. Radicioni