Semi Supervised Change Detection

Semi-supervised Change Detection is a technique in the field of computer vision that aims to detect changes in images or videos by utilizing a small amount of labeled data and a large amount of unlabeled data. Its goal is to improve the accuracy and efficiency of change detection while reducing reliance on costly labeled data. This method combines the strengths of supervised and unsupervised learning, enabling more robust change detection in various scenarios, with broad application value such as environmental monitoring, urban planning, and security surveillance.