Image classification

Core computer vision technology: It assigns a single, predefined categorical label (e.g., 'cat,' 'defective,' 'X-ray') to an entire input image.

Image classification is the process of training a machine learning model to categorize an image into one of its predefined classes. This is typically achieved using Convolutional Neural Networks (CNNs), which learn hierarchical features from the pixel data: think of models like ResNet or AlexNet. Key applications drive significant business value: Autonomous vehicles use it for real-time object identification (car, pedestrian, road), while manufacturing employs it for quality control (classifying products as 'defective' or 'market-ready'). In healthcare, the technology analyzes medical images (CT scans, X-rays) to assist in rapid disease diagnosis.

https://www.ibm.com/topics/image-classification