Gradient clustering algorithm based on deep learning aerial image detection

摘要: Abstract In recent years, computer vision, especially deep learning, has been widely used in various fields. Through the learning aerial image detection gradient clustering algorithm automatic recognition, it can solve limitations of manual shooting by humans, shoot from a high altitude to panoramic view specific area, and provide more comprehensive solution. The traditional forest resource management work is mainly carried out forestry personnel carry large number investigations on forest. This method not only consumes lot manpower material resources, but also does have real-time nature. It difficult deal with all kinds management. Problems, causing unnecessary losses. this regard, paper proposes an change based H-KFCM, designs related experiments verify demonstrate performance algorithm. paper, we conduct parallel study processing. By using CUDA (Compute Unified Device Architecture) perform large-scale processing data. Can greatly shorten time obtain results, improve efficiency relevant personnel. Experiment analysis. be seen results that parallelization program implemented faster calculation speed uses less high-resolution images, good acceleration ratio compared CPU.