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
CONNECT:
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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