This is lecture 4 of course 6.S094: Deep Learning for Self-Driving Cars (2018 version). This class is free and open to everyone. It is an introduction to the practice of deep learning through the applied theme of building a self-driving car.

OUTLINE:
0:00 - Computer Vision and Convolutional Neural Networks
22:15 - Network Architectures for Image Classification
34:39 - Fully Convolutional Neural Networks
44:35 - Optical Flow
50:07 - SegFuse Dynamic Scene Segmentation Competition

INFO:
Slides: http://bit.ly/2HdjksA
Website: https://deeplearning.mit.edu
GitHub: https://github.com/lexfridman/mit-deep-learning
Playlist: https://goo.gl/SLCb1y

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LINKS:
Playlist: https://goo.gl/SLCb1y
Lecture 1: Deep Learning - https://youtu.be/-6INDaLcuJY
Lecture 2: Self-Driving Cars - https://youtu.be/_OCjqIgxwHw
Lecture 3: Deep Reinforcement Learning - https://youtu.be/MQ6pP65o7OM
Lecture 4: Computer Vision - https://youtu.be/CLOAswsxudo
Lecture 5: Deep Learning for Human Sensing - https://youtu.be/Z2GfE8pLyxc

Guest talk: Sacha Arnoud, Waymo - https://youtu.be/LSX3qdy0dFg
Guest talk: Emilio Frazolli, nuTonomy - https://youtu.be/dWSbItd0HEA
Guest talk: Sterling Anderson, Aurora - https://youtu.be/HKBhP9JISF0

2017:
Guest talk: Sertac Karaman, MIT - https://youtu.be/0fLSf3NO0-s
Guest talk: Chris Gerdes, Stanford - https://youtu.be/LDprUza7yT4