Lecture

Hand Pose Estimation

Description

This lecture covers topics such as hand pose estimation from depth images, regression techniques, and the use of convolutional layers in neural networks. It discusses the evolution of image classification models from LeNet to VGG19 and the advancements in deep learning with architectures like ResNet and U-Net. The lecture also explores the application of neural networks in tasks like image classification, hand pose estimation, and AlphaGo's use of deep nets for strategic decision-making in the game of Go.

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