Towards robust deep learning models against corruptions
This thesis focuses on the crucial challenge of enhancing the resilience of deep learn- ing models against natural corruptions. Although deep learning models have the potential to bring about significant advancements in various fields, they are susceptible to failure when faced with scenarios that d...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/173647 |