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Consensus of Ambiguity: Theory of Active Learning for Biomedical Image Analysis Applications
Scott Doyle
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Oznake: computer science;bioinformatics;machine learning;active learning;computer vision;computational photography
Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous” samples, ensuring that each labeled sample is maximally informative. This is invaluable in applications where manual labeling is exp ...
Leto: 2010 Vir: videolectures.net
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