Understanding CNNs: Striding & Padding

1.What is a CNN?

A Convolutional Neural Network (CNN) is like a super-smart librarian who can look at pictures and figure out what’s in them — like spotting a dog, a car, or a tree. Instead of reading books, it “reads” images by scanning them with a tiny magnifying glass (called a filter or kernel). This magnifying glass slides over the picture, looking at small chunks at a time, and picks up clues like lines, corners, or colors. These clues help the CNN guess what the picture shows.

Simple Analogy: Imagine you’re doing a puzzle. You don’t look at the whole thing at once — you check small pieces to see how they fit. A CNN does the same with images.

A CNN is a type of artificial intelligence used mainly for processing images (like recognizing cats in photos).

When discussing Convolutional Neural Networks (CNNs), two key concepts are striding and padding. Let me explain these in simple terms.

2.Striding: What is it?

Striding is how big of a step the filter takes as it moves across the image. Think of it like hopping instead of sliding step-by-step.

• Stride = 1: The filter moves one pixel at a time. It looks at every little spot closely.
• Stride = 2: The filter…