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INFORMATICASI
2002
91views more  INFORMATICASI 2002»
13 years 9 months ago
Using Image Segmentation as a Basis for Categorization
Image categorization is the problem of classifying images into one or more of several possible categories or classes, which are defined in advance. Classifiers can be trained usin...
Janez Brank
ICCV
2005
IEEE
14 years 11 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICML
2009
IEEE
14 years 10 months ago
Compositional noisy-logical learning
We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
Alan L. Yuille, Songfeng Zheng
MCS
2009
Springer
14 years 2 months ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar
CVPR
2009
IEEE
15 years 4 months ago
Boosted Multi-Task Learning for Face Verification With Applications to Web Image and Video Search
Face verification has many potential applications including filtering and ranking image/video search results on celebrities. Since these images/videos are taken under uncontrolle...
Xiaogang Wang (MIT), Cha Zhang (Microsoft Research...