Explore advanced classification techniques in computer vision through this comprehensive lecture from the University of Central Florida's CAP5415 Computer Vision course. Delve into support vector machines (SVMs), including nonlinear SVMs and their advantages. Examine the machine learning framework, feature extraction, and neural networks, with a focus on fully convolutional networks and the conversion of fully connected layers to convolutional layers. Learn about various activation functions, binary and multi-label classification, loss functions, and optimization techniques like gradient descent. Gain insights into network training processes and visualize convolutional operations. This in-depth lecture equips you with essential knowledge for tackling complex classification problems in computer vision applications.
Classification in Computer Vision - Part II - Lecture 19