CNNs: from a beginner's point of view

DEV Community•Wednesday, November 12, 2025 at 6:09:12 PM

In the exploration of Convolutional Neural Networks (CNNs), the author shares insights from their repeated learning experiences, aiming to simplify the concept for beginners. CNNs are designed to mimic human visual recognition, allowing computers to interpret images without the cumbersome pixel-by-pixel analysis required by traditional neural networks. Prior to CNNs, image processing involved flattening images into long numerical lists, which proved inefficient, especially given the vast number of pixels in images—approximately 150,000 for a 224x224 pixel image. The complexity increases significantly with RGB images, which can contain around 450,000 numbers. CNNs address these challenges by utilizing layers that can learn and adapt, significantly reducing the number of weights that need to be processed. For instance, a first hidden layer with 1,000 neurons could involve 450 million weights, showcasing the scale at which CNNs operate. This advancement not only enhances image recognition…

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