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Thesis

Transfer learning for object category detection

Abstract:

Object category detection, the task of determining if one or more instances of a category are present in an image with their corresponding locations, is one of the fundamental problems of computer vision. The task is very challenging because of the large variations in imaged object appearance, particularly due to the changes in viewpoint, illumination and intra-class variance. Although successful solutions exist for learning object category detectors, they require massive amounts of traini...

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Research group:
Robotics Research Group, Visual Geometry Group
Oxford college:
Brasenose College
Role:
Author

Contributors

Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
Language:
English
Keywords:
Subjects:
UUID:
uuid:c9e18ff9-df43-4f67-b8ac-28c3fdfa584b
Local pid:
ora:8880
Deposit date:
2014-08-18

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