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CVPR
2008
IEEE
16 years 5 months ago
Learning for stereo vision using the structured support vector machine
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
Yunpeng Li, Daniel P. Huttenlocher
ICIP
2000
IEEE
16 years 4 months ago
Pyramid Texture Compression and Decompression Using Interpolative Vector Quantization
Abstract-Texture mapping is a common technique used to increase the visual quality of 3D scenes. As texture mapping requires large memory to deal with large textures generally r e ...
Young-Su Kwon, In-Cheol Park, Chong-Min Kyung
ICPR
2004
IEEE
16 years 4 months ago
Group-based Relevance Feedback with Support Vector Machine Ensembles
Support vector machines (SVMs) have become one of the most promising techniques for relevance feedback in content-based image retrieval (CBIR). Typical SVM-based relevance feedbac...
Chu-Hong Hoi, Michael R. Lyu
ICML
2004
IEEE
16 years 4 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
KDD
2002
ACM
160views Data Mining» more  KDD 2002»
16 years 3 months ago
Scaling multi-class support vector machines using inter-class confusion
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
Shantanu Godbole, Sunita Sarawagi, Soumen Chakraba...