Active Learning to Recognize Multiple Types of Plankton

Authors:
Tong Luo;Kurt Kramer;Dmitry B. Goldgof;Lawrence O. Hall;Scott Samson;Andrew Remsen;Thomas Hopkins
Affiliations:
University of South Florida, Tampa, FL;University of South Florida, Tampa, FL;University of South Florida, Tampa, FL;University of South Florida, Tampa, FL;University of South Florida, St. Petersburg, FL;University of South Florida, St. Petersburg, FL;University of South Florida, St. Petersburg, FL
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Year:
2004

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Abstract

Active learning has been applied with support vector machines to reduce the data labeling effort in pattern recognition domains. However, most of those applications only deal with two class problems. In this paper, we extend the active learning approach to multiple class support vector machines. The experimental results from a plankton recognition system indicate that our approach often requires significantly less labeled images to maintain the same accuracy level as random sampling.