MIT 6.S191: Convolutional Neural Networks
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- Опубликовано: 6 июн 2024
- MIT Introduction to Deep Learning 6.S191: Lecture 3
Convolutional Neural Networks for Computer Vision
Lecturer: Alexander Amini
* New 2024 Edition *
For all lectures, slides, and lab materials: introtodeeplearning.com
Lecture Outline
0:00 - Introduction
2:45 - Amazing applications of vision
4:56 - What computers "see"
13:09- Learning visual features
18:53 - Feature extraction and convolution
22:12 - The convolution operation
28:38 - Convolution neural networks
37:10 - Non-linearity and pooling
41:23 - End-to-end code example
43:21 - Applications
46:14 - Object detection
57:10 - End-to-end self driving cars
1:06:15 - Summary
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Thank you for sharing quality content like this for free for several years
Thanks for sharing this knowledge. Be blessed
I wanted to extend my sincere thanks for the wonderful lecture you delivered on Deep Learning.
thank for sharing that course , that's so usefull !
Waiting patiently
That's the spirit
Thank you very much, it is a great lecture. I hope that you develop the lectures over the years as it seems to be the same contents. topics like pretrained models and knowledge transfer, YOLO might be good to be added to CNN
While sliding window is good, YoLo outperforms Faster RCNN and is generally considered state of the art for object detection
Waiting ..
Cant wait...
Software Lab 1 still not made available, when will that happen?
It is published now
Where is the software lab?
Have any of the labs been published yet?
yes
But the lab between Lecture 2 and 3 is still not published in the website?
I think it is not their practice to publish their lab work
It has been published now
right?
Thank you for sharing, please i need a help and i send an email to you but no response, could you please help me?
thanks in advance.
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