Exploring images with deep learning for classification, retrieval and synthesis

Leiden Repository

Exploring images with deep learning for classification, retrieval and synthesis

Type: Doctoral Thesis
Title: Exploring images with deep learning for classification, retrieval and synthesis
Author: Liu, Y.
Issue Date: 2018-10-24
Keywords: Computer Vision
Multimedia Applications
Deep Learning
Abstract: In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually. Thus, it becomes challenging to mine semantic information from such a huge amount of visual data. To solve this challenge, deep learning, an important sub-field in machine learning, has achieved impressive developments in recent years. Inspired by its success, this thesis aims to develop new approaches in deep learning to explore and analyze image data from three research themes: classification, retrieval and synthesis. In summary, the research of this thesis contributes at three levels: models and algorithms, practical scenarios and empirical analysis. First, this work presents new approaches based on deep learning to address eight research questions regarding the three themes. In addition, it aims towards adapting the approaches to practical scenarios in real world. Furthermore, this thesis provides numerous experiments and in-depth analysis, which can help motivate further research on the three research themes. Computer Vision Multimedia Applications Deep Learning
Promotor: Supervisor: Kok J.N., Lew M.S.
Faculty: Faculty of Science
University: Leiden University
Uri: urn:isbn:9789463751391
Handle: http://hdl.handle.net/1887/66480
 

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application/pdf Conclusions 252.5Kb View/Open
application/pdf Bibliography_Abbreviations 238.7Kb View/Open
application/pdf Summary in English 133.0Kb View/Open
application/pdf Summary in Dutch 133.6Kb View/Open
application/pdf Curriculum Vitae 131.9Kb View/Open
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