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ICPR
2008
IEEE
14 years 1 months ago
Semi-supervised discriminant analysis based on UDP regularization
We propose a semi-supervised learning algorithm for discriminant analysis, which uses the geometric structure of both labeled and unlabeled samples and perform a manifold regulari...
Huining Qiu, Jian-Huang Lai, Jian Huang, Yu Chen
ICDAR
2009
IEEE
13 years 5 months ago
Unconstrained Handwritten Document Layout Extraction Using 2D Conditional Random Fields
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
Florent Montreuil, Emmanuele Grosicki, Laurent Heu...
ICMCS
2010
IEEE
198views Multimedia» more  ICMCS 2010»
13 years 8 months ago
Naming persons in news video with label propagation
Labeling persons appearing in video frames with names detected from the video transcript helps improving the video content identification and search task. We develop a face naming...
Phi The Pham, Marie-Francine Moens, Tinne Tuytelaa...
IGARSS
2009
13 years 5 months ago
Active Learning of Hyperspectral Data with Spatially Dependent Label Acquisition Costs
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Alexander Liu, Goo Jun, Joydeep Ghosh
DAGM
2004
Springer
14 years 25 days ago
Learning from Labeled and Unlabeled Data Using Random Walks
We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to...
Dengyong Zhou, Bernhard Schölkopf