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Thesis

Large-scale learning of discriminative image representations

Abstract:

This thesis addresses the problem of designing discriminative image representations for a variety of computer vision tasks. Our approach is to employ large-scale machine learning to obtain novel representations and improve the existing ones. This allows us to propose descriptors for a variety of applications, such as local feature matching, image retrieval, image classification, and face verification. Our image and region descriptors are discriminative, compact, and achieve state-of-t...

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Department:
MPLS, Engineering Science
Role:
Author, Copyright Holder

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Role:
Supervisor
Role:
Supervisor
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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