Investigating the causes of the vulnerability of CNNs to adversarial perturbations: learning objective, model components, and learned representations
This work focuses on understanding how adversarial perturbations can disrupt the behavior of Convolutional Neural Networks (CNNs). Here, it is hypothesized that some components may be more vulnerable than others, unlike other research that considers a model vulnerable as a whole. Identifying model-s...
محفوظ في:
المؤلف الرئيسي: | |
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مؤلفون آخرون: | |
التنسيق: | Thesis-Master by Research |
اللغة: | English |
منشور في: |
Nanyang Technological University
2023
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الموضوعات: | |
الوصول للمادة أونلاين: | https://hdl.handle.net/10356/171336 |
الوسوم: |
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المؤسسة: | Nanyang Technological University |
اللغة: | English |