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PRIB
2010
Springer
242views Bioinformatics» more  PRIB 2010»
13 years 5 months ago
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Scott Doyle, Anant Madabhushi
MIR
2005
ACM
198views Multimedia» more  MIR 2005»
14 years 29 days ago
Semi-automatic video annotation based on active learning with multiple complementary predictors
In this paper, we will propose a novel semi-automatic annotation scheme for video semantic classification. It is well known that the large gap between high-level semantics and low...
Yan Song, Xian-Sheng Hua, Li-Rong Dai, Meng Wang
CCIA
2005
Springer
14 years 28 days ago
Classifying Natural Objects on Outdoor Scenes
We propose an hybrid and probabilistic classification of image regions belonging to scenes primarily containing natural objects, e.g. sky, trees, etc. as a first step in solving ...
Anna Bosch, Xavier Muñoz, Joan Martí...
ICML
2006
IEEE
14 years 8 months ago
Active sampling for detecting irrelevant features
The general approach for automatically driving data collection using information from previously acquired data is called active learning. Traditional active learning addresses the...
Sriharsha Veeramachaneni, Emanuele Olivetti, Paolo...
ICML
2009
IEEE
14 years 8 months ago
Uncertainty sampling and transductive experimental design for active dual supervision
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
Vikas Sindhwani, Prem Melville, Richard D. Lawrenc...