Towards robust explainability of deep neural networks against attribution attacks
Deep learning techniques have been rapidly developed and widely applied in various fields. However, the black-box nature of deep neural networks (DNNs) makes it difficult to understand their decision-making process, giving rise to the field of explainable artificial intelligence (XAI). Attribution m...
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格式: | Thesis-Doctor of Philosophy |
語言: | English |
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Nanyang Technological University
2024
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在線閱讀: | https://hdl.handle.net/10356/175394 |
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機構: | Nanyang Technological University |
語言: | English |