A multitarget detection method for laser remote sensing images based on machine learning

The laser remote sensing technology, known for its high accuracy and excellent resolution, has found widespread application in various fields such as geographic information systems, environmental monitoring, and urban planning. As the amount of remote sensing data increases, challenges arise in the efficient and accurate detection of multiple targets from laser remote sensing images. In the present work, a multi-target detection method for laser remote sensing images based on machine learning is developed, in which the transfer learning, selection of feature extraction networks, and optimization of the Region Proposal Network (RPN) are explored.