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What are Convolutional Neural Networks? | IBM
What are Convolutional Neural Networks? | IBM
Oct 6, 2021
ibm.com
Convolutions are mathematical operations at the heart of deep learning, especially within convolutional neural networks (CNNs). They operate by moving a small grid of numbers, known as a kernel or filter, across an input image to identify meaningful patterns like edges, textures, and shapes. At every position, the kernel multiplies its values with the corresponding pixels, then sums the results to produce a single number. Repeating this across the image creates a feature map that emphasizes spec
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Artificial Intelligence | AI on Instagram: "A convolutional layer works by applying small, learnable filters (also called kernels) across the input image (or the previous layer’s output). Think of a filter as a tiny grid of numbers (e.g., 5x5) that acts as a feature detector; its weights are trained to “look” for a single, specific pattern, like a vertical edge, a specific color, or a simple texture. The layer “slides” this filter over every possible patch of the input. At each position, it perf
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