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» A Training Method with Small Computation for Classification
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ANCS
2006
ACM
14 years 27 days ago
Packet classification using coarse-grained tuple spaces
While the problem of high performance packet classification has received a great deal of attention in recent years, the research community has yet to develop algorithmic methods t...
Haoyu Song, Jonathan S. Turner, Sarang Dharmapurik...
CVPR
2010
IEEE
13 years 11 months ago
Proximate Sensing: Inferring What-Is-Where From Georeferenced Photo Collections
The primary and novel contribution of this work is the conjecture that large collections of georeferenced photo collections can be used to derive maps of what-is-where on the surf...
Daniel Leung, Shawn Newsam
CVPR
2008
IEEE
14 years 11 months ago
In defense of Nearest-Neighbor based image classification
State-of-the-art image classification methods require an intensive learning/training stage (using SVM, Boosting, etc.) In contrast, non-parametric Nearest-Neighbor (NN) based imag...
Oren Boiman, Eli Shechtman, Michal Irani
ACCV
2010
Springer
13 years 4 months ago
Descriptor Learning Based on Fisher Separation Criterion for Texture Classification
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Yimo Guo, Guoying Zhao, Matti Pietikäinen, Zh...
ECCV
2008
Springer
14 years 11 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher