The Semantic Segmentation Of Remote Sensing

Semantic segmentation in remote sensing refers to the classification of each pixel in an image through deep learning technology to identify and distinguish different land cover categories. Its goal is to achieve high-precision land cover recognition and boundary localization, providing detailed surface coverage information. This technology has significant application value in urban planning, environmental monitoring, disaster assessment, and other fields, supporting decision-makers in conducting precise analysis and management.