Link to the course page for all the relevant material: https://subrahmanyamgorthi.weebly.com/machine-learning-for-image-processing.html
This lecture discusses how CNN works and its relation to the conventional convolution-based linear filters. The block diagram illustrating various steps in classification is revisited. Bayesian classification and feature vectors are introduced in this lecture.
Video Index:
00:00 - Recap of image processing module and why CNN works?
14:15 - Process flow in MLIP
21:05 - Classifier design - Introduction
26:00 - Bayesian classification introduction
35:50 - Description of feature vectors
