Triplet-Based Semantic Relation Learning for Aerial Remote Sensing Image Change Detection
Triplet-Based Semantic Relation Learning for Aerial Remote Sensing Image Change Detection is a scholarly work, published in 2019 in ''IEEE Geoscience and Remote Sensing Letters''. The main subjects of the publication include image, artificial intelligence, computer science, aerial image, computer vision, remote sensing, relation, feature, set, pixel, pattern recognition, change detection, and hyperspectral imaging. This letter presents a novel supervised change detection method based on a deep siamese semantic network framework, which is trained by using improved triplet loss function for optical aerial images.