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1
Intro
2
Course Project
3
deliverables
4
discussion
5
Questions
6
Classification
7
Features
8
Functions
9
Linear Classification
10
Nearest Neighbor
11
Testing Sample
12
Pop Quiz
13
Decision Boundary
14
Algorithm
15
Problems
16
Linear Classifier
17
Maximum Margin Classifier
Description:
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.

Classification in Computer Vision - Lecture 18

University of Central Florida
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