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