Investigating robustness of deep learning against adversarial examples
Deep learning has achieved many unprecedented performances in various fields, such as the field of Computer Vision. Deep neural networks have shown many impressive results in solving complex problems, yet, they are still vulnerable to adversarial attacks, which come in the form of subtle, often impe...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2019
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| Online Access: | https://hdl.handle.net/10356/136558 |