Quick Summary
Convolutional neural networks detect faces by scanning images with learned filters, proposing candidate regions, and classifying them into precise bounding boxes and keypoints. They do this in real time for both still images and live video, and they have largely replaced older hand-crafted approaches like Viola–Jones.
This article explains how the pipeline works, why CNNs can recognize a face, and how modern models handle masks, low light, and edge hardware.
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