Convolutional Neural Networks for Computer Vision - MIT 6.S191 Lecture 3

Explore the fundamentals of Convolutional Neural Networks (CNNs) for computer vision in this lecture from MIT's Introduction to Deep Learning course (6.S191). Alexander Amini delivers this comprehensive 2025 edition lecture covering CNN architecture, principles, and applications in computer vision. Learn how these specialized neural networks process visual data through convolutional layers, pooling operations, and fully connected layers to perform tasks like image classification and object detection. The lecture provides both theoretical foundations and practical insights into implementing CNNs for visual recognition tasks. Part of MIT's complete deep learning curriculum with additional resources available on the course website.