Image datasets are collections of images used for training and evaluating machine learning models, particularly in computer vision tasks. These datasets can contain thousands or millions of images, often labeled with relevant information such as categories or annotations. They help researchers and developers improve algorithms for tasks like object recognition, image classification, and segmentation. Common examples of image datasets include ImageNet, CIFAR-10, and MNIST. Each dataset serves different purposes and challenges, providing a standardized way to benchmark model performance. Access to diverse and well-structured image datasets is crucial for advancing the field of artificial intelligence.