Perception and Learning for Autonomous Driving - Part 1

Perception and Learning for Autonomous Driving - Part 1

Institute for Pure & Applied Mathematics (IPAM) via YouTube Direct link

Sensor Suite

3 of 21

3 of 21

Sensor Suite

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Classroom Contents

Perception and Learning for Autonomous Driving - Part 1

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  1. 1 Intro
  2. 2 Robust Multi-modal Perception
  3. 3 Sensor Suite
  4. 4 Perception and Learning for Autonomous Driving
  5. 5 Deep Neural Networks / DNNS
  6. 6 Convolutional networks
  7. 7 Convolutional Neural Networks
  8. 8 Single Layer Architecture
  9. 9 Deep Learning
  10. 10 Classification, Detection, and Segmentation
  11. 11 Architectures Evolution
  12. 12 Factorized convolution
  13. 13 Parameters and computation
  14. 14 Residual Networks
  15. 15 Classification Detection, and Segmentation
  16. 16 Challenges of object detection?
  17. 17 Conceptual approach: Sliding window detection
  18. 18 PASCAL VOC Challenge (2006-2012)
  19. 19 R-CNN details
  20. 20 Fast R-CNN training
  21. 21 Multi-task loss

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