How Convolutions Actually Work in Deep Learning

Описание: Ever wondered how machines see images or spot patterns in data?

Let's break down how convolutions - the engine behind CNNs (Convolutional Neural Networks) actually work in deep learning and image processing.

A convolution works by applying a filter (also called a kernel) to a grid of numbers, like a matrix or image, to detect key patterns. As the filter slides across the input, it multiplies matching elements, sums them, and produces new values that reveal edges, shapes, or even textures.

This simple yet powerful process helps neural networks capture low-level details in the early layers and complex features like faces, objects, or handwriting in deeper ones.

C: 3blue1brown

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