Dive into the world of Convolutional Neural Networks for Computer Vision in this comprehensive lecture from MIT's Introduction to Deep Learning course. Explore amazing applications of vision, understand what computers "see," and learn about visual feature extraction. Delve into the convolution operation, the architecture of convolutional neural networks, and the importance of non-linearity and pooling. Witness an end-to-end code example and discover practical applications, including object detection and self-driving cars. This 56-minute lecture, delivered by Alexander Amini in January 2021, provides a thorough overview of CNNs and their role in advancing computer vision technology.
Overview
Syllabus
​ - Introduction
​ - Amazing applications of vision
- What computers "see"
- Learning visual features
​ - Feature extraction and convolution
- The convolution operation
​ - Convolution neural networks
​ - Non-linearity and pooling
- End-to-end code example
​ - Applications
- Object detection
- End-to-end self driving cars
​ - Summary
Taught by
https://www.youtube.com/@AAmini/videos
