INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS
Ph.D
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2023
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sg-nus-scholar.10635-2386352023-03-31T18:00:53Z INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS WANG WEIXI MATHEMATICS Hui Ji Self-supervised Learning, Computer vision, Monte Carlo, Langevin dynamics, Optimization, Inverse problem Ph.D DOCTOR OF PHILOSOPHY (FOS) 2023-03-31T18:00:53Z 2023-03-31T18:00:53Z 2022-12-13 Thesis WANG WEIXI (2022-12-13). INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS. ScholarBank@NUS Repository. https://scholarbank.nus.edu.sg/handle/10635/238635 0009-0007-1586-1355 en |
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National University of Singapore |
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NUS Library |
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Asia |
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Singapore Singapore |
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NUS Library |
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ScholarBank@NUS |
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English |
topic |
Self-supervised Learning, Computer vision, Monte Carlo, Langevin dynamics, Optimization, Inverse problem |
spellingShingle |
Self-supervised Learning, Computer vision, Monte Carlo, Langevin dynamics, Optimization, Inverse problem WANG WEIXI INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS |
description |
Ph.D |
author2 |
MATHEMATICS |
author_facet |
MATHEMATICS WANG WEIXI |
format |
Theses and Dissertations |
author |
WANG WEIXI |
author_sort |
WANG WEIXI |
title |
INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS |
title_short |
INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS |
title_full |
INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS |
title_fullStr |
INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS |
title_full_unstemmed |
INVERSE PROBLEMS IN IMAGING: FROM REGULARIZATION METHODS TO SELF-SUPERVISED LEARNING METHODS |
title_sort |
inverse problems in imaging: from regularization methods to self-supervised learning methods |
publishDate |
2023 |
url |
https://scholarbank.nus.edu.sg/handle/10635/238635 |
_version_ |
1762031091097534464 |