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MIT 6.S094: Computer Vision
5 segments available
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 CONNECT: - If you enjoyed this video, please subscribe to this channel. - AI Podcast: https://lexfridman.com/ai/ - Show your support: https://www.patreon.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Twitter: https://twitter.com/lexfridman - Facebook: https://www.facebook.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - Slack: https://deep-mit-slack.herokuapp.com 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
Segments Timeline
Computer Vision and Convolutional Neural Networks
"today we'll talk about how to make machines see computer vision and we'll present Thank You Claire said yes and today we will present a competition that unlike deep traffic which is designed to explor..."
Network Architectures for Image Classification
"let's take image net as a case study an image net the data set an image net the challenge the task is classification as I mentioned the first lecture image net is a data set one of the largest in the ..."
Fully Convolutional Neural Networks
"combos in your networks chop off the final layer in order to apply to a particular domain and that is what we'll do with fully convolutional neural networks the ones that we task to segment the image ..."
Optical Flow
"the other aspect here that everything we've talked about from the classification to the segmentation to making sense of images is it there the information about time the temporal dynamics of the scene..."
SegFuse Dynamic Scene Segmentation Competition
"so using flow net 2.0 here's the data set we're making available for psych fuse the competition cars that mit.edu slash psych fuse first the original video us driving in high-definition 1080p and a 8k..."