Modern Convolutional Networks and Image Recognition

This lecture covers the evolution of deep convolutional networks in the context of image recognition, focusing on the breakthroughs in the ImageNet competitions. It discusses the development of networks like AlexNet, ResNet, and Inception modules, highlighting their impact on improving image recognition accuracy. The lecture also explores the concept of transfer learning for image recognition, showcasing how pre-trained models can be adapted to new tasks with high accuracy.