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Published 2008 | Published
Book Section - Chapter Open

Entropy-based active learning for object recognition

Abstract

Most methods for learning object categories require large amounts of labeled training data. However, obtaining such data can be a difficult and time-consuming endeavor. We have developed a novel, entropy-based ldquoactive learningrdquo approach which makes significant progress towards this problem. The main idea is to sequentially acquire labeled data by presenting an oracle (the user) with unlabeled images that will be particularly informative when labeled. Active learning adaptively prioritizes the order in which the training examples are acquired, which, as shown by our experiments, can significantly reduce the overall number of training examples required to reach near-optimal performance. At first glance this may seem counter-intuitive: how can the algorithm know whether a group of unlabeled images will be informative, when, by definition, there is no label directly associated with any of the images? Our approach is based on choosing an image to label that maximizes the expected amount of information we gain about the set of unlabeled images. The technique is demonstrated in several contexts, including improving the efficiency of Web image-search queries and open-world visual learning by an autonomous agent. Experiments on a large set of 140 visual object categories taken directly from text-based Web image searches show that our technique can provide large improvements (up to 10 x reduction in the number of training examples needed) over baseline techniques.

Additional Information

U.S. Government work not protected by U.S. copyright. This research has been carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration (NASA). Funding provided under the Applied Information Systems Research Program. A.H. and P.P. were supported by N00014-06-1- 0734.

Attached Files

Published - Holub2008p84382008_Ieee_Computer_Society_Conference_On_Computer_Vision_And_Pattern_Recognition_Workshops_Vols_1-3.pdf

Files

Holub2008p84382008_Ieee_Computer_Society_Conference_On_Computer_Vision_And_Pattern_Recognition_Workshops_Vols_1-3.pdf

Additional details

Created:
August 19, 2023
Modified:
October 20, 2023