Bi Temporal Image

Bi-temporal image analysis focuses on identifying changes between two images of the same location taken at different times, primarily using remote sensing data. Current research emphasizes developing deep learning models, including Siamese networks, transformers, and generative adversarial networks, to improve change detection accuracy and efficiency, often addressing challenges like data scarcity and domain shifts through semi-supervised or unsupervised learning techniques. This field is crucial for monitoring environmental changes, urban development, and disaster response, offering valuable insights for various scientific disciplines and practical applications. The development of lightweight and efficient models is also a key focus, particularly for on-board processing of large-scale datasets.