Remote Sensing Image

Remote sensing image analysis focuses on extracting meaningful information from images captured by satellites and aerial platforms, primarily for Earth observation applications. Current research emphasizes improving the accuracy and efficiency of various tasks, including semantic segmentation, object detection (especially oriented objects), and change detection, often leveraging deep learning models like transformers and UNets, along with innovative techniques such as prompt learning and multimodal fusion. These advancements are crucial for a wide range of applications, from precision agriculture and urban planning to environmental monitoring and disaster response, enabling more accurate and timely insights from remotely sensed data.