Patch Based

Patch-based methods are transforming various fields by processing data in smaller, manageable units, improving efficiency and addressing challenges in large datasets. Current research focuses on optimizing patch selection and processing, employing techniques like attention mechanisms, and integrating patch-level information with larger model architectures such as transformers and Siamese networks. This approach is proving particularly valuable in image analysis tasks, including medical image analysis, anomaly detection, and remote sensing, where it enhances accuracy, reduces computational costs, and improves model robustness.