CNN

Convolutional Neural Networks (CNNs) are designed to help machines understand visual information.

This section focuses on how CNNs extract spatial features from images using convolutional filters, pooling layers, and hierarchical feature learning. The projects here emphasize real-world computer vision pipelines rather than isolated experiments.

The goal is to understand how raw pixels transform into meaningful representations that enable tasks like scene classification, object recognition, and visual pattern detection.