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  5. Mouse behavior recognition with the wisdom of crowd

Mouse behavior recognition with the wisdom of crowd

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Author(s)
Ni, Yuzhao
Advisor(s)
Tomaso Poggio.
Date Issued
2013
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, we designed and implemented a crowdsourcing system to annotate mouse behaviors in videos; this involves the development of a novel clip-based video labeling tools, that is more efficient than traditional labeling tools in crowdsourcing platform, as well as the design of probabilistic inference algorithms that predict the true labels and the workers' expertise from multiple workers' responses. Our algorithms are shown to perform better than majority vote heuristic. We also carried out extensive experiments to determine the effectiveness of our labeling tool, inference algorithms and the overall system.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 67-72).
Subjects
Computation for Design and Optimization Program.
MIT Department
Massachusetts Institute of Technology. Computation for Design and Optimization Program
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M.I.T. theses are protected by
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permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
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http://hdl.handle.net/1721.1/82415
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