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

Aiming at the problems of low recognition accuracy and high false detection rate and missing rate of the current mainstream target detection algorithms in the background of real aerial battlefield data, the Yolo target recognition algorithm is studied,A lightweight aerial military target detection model based on improved Yolov5n is proposed,Firstly, ECA attention mechanism is integrated with C3 module of backbone network to solve the problem of complex background and similar object interference in aerial images.Secondly, the CIoU loss function is replaced by A Normalized Gaussian Wasserstein Distance (NWD) to improve the detection and recognition of fuzzy small targets.Finally, GSConv lightweight convolution is used instead of standard convolution to reduce the weight of the model. Through experimental tests, the average detection accuracy of the improved algorithm model reaches 81.5%, an increase of 0.9%, the model size is 3.4MB, reduced 0.4MB, the recognition speed is 113 frames per second.The experimental results show that the model is lightweight while maintaining high precision aerial military target detection.