Convolutional Neural Networks in Computer Vision | Image Classification

Описание: @Neuneworks
convolutional neural networks in computer vision
In this video, we’ll explore Computer Vision, a powerful branch of Artificial Intelligence (AI) that helps machines understand and process images just like humans do. You’ll learn how Convolutional Neural Networks (CNNs) work behind the scenes to analyze, classify, and recognize images.

We’ll cover key concepts including:
✅ What is Computer Vision in AI
✅ How images are represented as numerical data (RGB, pixels, matrices)
✅ What convolution, filters, and feature extraction mean
✅ Techniques like Padding, Pooling, and Striding
✅ How CNNs perform image classification
✅ Overview of models like CNN, GAN, Diffusion, Vision Transformers, and Vision-Language Models

By the end of this video, you’ll understand how deep learning models process image data and how CNNs form the foundation of modern Computer Vision systems.

📘 Topics Covered:

Image Representation in AI

Convolution Operation Explained

Edge Detection using Filters (Prewitt, Laplacian, etc.)

Pooling and Striding in CNN

Building a Simple CNN for Image Classification using CIFAR Dataset

🎥 Watch till the end to see how CNNs extract image features and convert them into meaningful predictions!
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00:00 Introduction
00:40 Imageprocessing intro
03:20 Feature Extraction
04:06 Edge Detection
05:51 Padding
06:10 Striding
06:27 Pooling
07:21 Demo