Introduction to Adversarial Attacks in Machine Learning - Lecture 1

Introduction to Adversarial Attacks in Machine Learning - Lecture 1

UCF CRCV via YouTube Direct link

Adversarial Attack on Semantic Segmentation

4 of 23

4 of 23

Adversarial Attack on Semantic Segmentation

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Classroom Contents

Introduction to Adversarial Attacks in Machine Learning - Lecture 1

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  1. 1 Intro
  2. 2 Attacks in the Real World
  3. 3 Fooling Face Recognition (Impersonation)
  4. 4 Adversarial Attack on Semantic Segmentation
  5. 5 Semantic Segmentation and Object Detection
  6. 6 Changing facial attributes and Gender
  7. 7 Adversarial attack on mobile phone cameras
  8. 8 Attack on a 3D-printed turtle
  9. 9 Attack on 3D Object Detection
  10. 10 Project Description
  11. 11 Terminology
  12. 12 Vector operations
  13. 13 Norms (Unit Ball)
  14. 14 Fast Gradient Sign Method (FGSM)
  15. 15 Momentum Iterative FGSM (MI-FGSM)
  16. 16 Projected Gradient Descent PGD
  17. 17 L-BFGS (Limited memory BFGS: Broyden-Fletcher-Goldfarb-Shanno algorithm)
  18. 18 Carlini and Wagner (C&W)
  19. 19 DeepFool (Binary Affine Classifier)
  20. 20 DeepFool (Binary Classifier)
  21. 21 DeepFool (Multi-Class Classifier)
  22. 22 Last Two Topics
  23. 23 Slides Credits

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