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KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 7 months ago
On updates that constrain the features' connections during learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Jian Huang 0002
SDM
2008
SIAM
140views Data Mining» more  SDM 2008»
13 years 9 months ago
Large-Scale Many-Class Learning
In many multiclass learning scenarios, the number of classes is relatively large (thousands,...), or the space and time efficiency of the learning system can be crucial. We invest...
Omid Madani, Michael Connor
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 12 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
IPMI
2007
Springer
14 years 8 months ago
Learning Best Features and Deformation Statistics for Hierarchical Registration of MR Brain Images
A fully learning-based framework has been presented for deformable registration of MR brain images. In this framework, the entire brain is first adaptively partitioned into a numbe...
Guorong Wu, Feihu Qi, Dinggang Shen
ICPR
2008
IEEE
14 years 8 months ago
Human tracking based on Soft Decision Feature and online real boosting
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
Hironobu Fujiyoshi, Masato Kawade, Shihong Lao, Ta...