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Adversarial Attacks and Defence by dakshjkhadalpur177 is a document available to read on EtoBox.
What is Adversarial Attacks and Defence about?
The document discusses adversarial attacks in machine learning, detailing various methods and techniques used to manipulate model inputs to achieve misclassification. It covers the creation of adversarial examples, the geometry of input space, and different types of attacks such as FGSM, PGD, and Deepfool, along with their implications for model robustness and security. Additionally, it outlines the taxonomy of attacks, including model-based, evasion, and poisoning attacks.
- Author
- dakshjkhadalpur177
- Language
- EN