Semantic Segmentation Of Orthoimagery

Semantic Segmentation of Orthoimagery refers to the pixel-level classification of orthoimages using deep learning and other technologies to identify and label different land cover categories in the images. Its goal is to achieve high-precision land cover recognition and spatial information extraction, providing crucial data support for urban planning, land use, environmental monitoring, and other fields. While this technology also has similar applications in medical image analysis, its primary value lies in the advancement and development of geographic information science and remote sensing technology.