Computer vision works by analyzing visual data (images or videos) using algorithms and AI models. It involves preprocessing images, extracting features, and interpreting these features to perform tasks like classification, detection, or segmentation.
Techniques like convolutional neural networks (CNNs) enable automated feature extraction and pattern recognition, making computer vision systems effective in applications such as facial recognition, object detection, and medical imaging.
Applications range from autonomous vehicles and surveillance systems to e-commerce and augmented reality, showcasing its versatility across industries.