Image recognition works by processing images to identify objects, patterns, or scenes. The process starts with preprocessing, such as resizing or normalizing the image, followed by feature extraction using algorithms or neural networks like CNNs.
The extracted features are compared to a trained model, which classifies the image or detects specific objects. Modern techniques leverage deep learning to automate feature extraction and improve accuracy.
Applications include identifying faces, detecting objects in real-time, and analyzing visual data for industries like healthcare, retail, and security.