国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

There are a large number of small targets in remote sensing images. Accurate detection of them is the basis of remote target recognition and tracking. In order to provide effective auxiliary tools for remote tracking, the micro target detection method of remote sensing image is optimized with the technical support of deep learning algorithm. The hardware equipment is used to collect the remote sensing image containing micro targets in real time, and the preprocessing of the initial image is completed through the steps of geometric correction, gray conversion, noise suppression, defogging and image enhancement. Through the segmentation of foreground and background image, the target to be detected in remote sensing image is selected. The deep convolution neural network is constructed as the operation environment of the deep learning algorithm, and the remote sensing image features are extracted through forward propagation and back propagation. Finally, through feature matching, the detection results including the number of small targets and position coordinates are obtained. Through the performance test experiment, it is concluded that compared with the traditional remote sensing image target detection method, the precision and recall of the optimal design method are increased by 6.3% and 10.74% respectively, the target position detection error is significantly reduced, and the response time is shortened by 2440ms, which proves that the optimal design method has good detection performance.