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DAGM
2004
Springer
15 years 3 months 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
CIVR
2003
Springer
126views Image Analysis» more  CIVR 2003»
15 years 3 months ago
Learning in Region-Based Image Retrieval
In this paper, several effective learning algorithms using global image representations are adjusted and introduced to region-based image retrieval (RBIR). First, the query point m...
Feng Jing, Mingjing Li, Lei Zhang, HongJiang Zhang...
JMLR
2010
121views more  JMLR 2010»
14 years 4 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
ICMCS
2006
IEEE
131views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Self-Supervised Learning for Robust Video Indexing
The performance of video analysis and indexing algorithms strongly depends on the type, content and recording characteristics of the analyzed video. Current video indexing approac...
Ralph Ewerth, Bernd Freisleben
ICRA
2008
IEEE
229views Robotics» more  ICRA 2008»
15 years 4 months ago
Learning of moving cast shadows for dynamic environments
Abstract— We propose a novel online framework for detecting moving shadows in video sequences using statistical learning techniques. In this framework, Support Vector Machines ar...
Ajay J. Joshi, Nikolaos Papanikolopoulos