Classification in Computer Vision - Lecture 18

Dive into the fundamentals of classification in computer vision with this comprehensive lecture from the University of Central Florida's CAP5415 Computer Vision course. Explore key concepts including feature extraction, linear classification, nearest neighbor algorithms, decision boundaries, and maximum margin classifiers. Learn how to approach classification problems and understand the importance of testing samples in machine learning. Gain insights into the mathematical foundations of computer vision and their practical applications in image classification and object detection. Enhance your understanding of deep learning techniques for computer vision and prepare for hands-on project work in this cutting-edge field.

Intro
Course Project
deliverables
discussion
Questions
Classification
Features
Functions
Linear Classification
Nearest Neighbor
Testing Sample
Pop Quiz
Decision Boundary
Algorithm
Problems
Linear Classifier
Maximum Margin Classifier