Change Detection

Change detection, the process of identifying differences between images of the same scene taken at different times, aims to automatically analyze and quantify these changes. Current research focuses on improving accuracy and efficiency using various deep learning architectures, including convolutional neural networks (CNNs), transformers, and diffusion models, often incorporating techniques like multimodal learning and self-supervised training to address data limitations. These advancements have significant implications for diverse applications such as environmental monitoring, urban planning, disaster response, and autonomous driving, enabling more efficient and accurate analysis of dynamic processes.