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

In order to improve the detection and recognition ability of key target points in weak texture images, a method of identifying and locating key target points in weak texture images based on deep learning is proposed. The topological feature distribution model of key target points of weak texture images with low light intensity is constructed. The transmittance is used as the detection coefficient, and the pixel big data distribution set is established by combining the prior knowledge of bright channels. The dark primary color fusion and RGB pixel decomposition methods are used to realize the information adaptive enhancement processing of weak texture images with low light intensity. According to the results of noise fusion and matching in the transmission area, the cross combination filter detection and deep learning algorithm are adopted to realize the noise reduction and information enhancement of the weak texture image with low light intensity, thus realizing the key target point detection and recognition of the weak texture image with low light intensity. Simulation results show that this method has high positioning recognition accuracy, with an average of 0.93, and good image output quality, with an average peak signal-to-noise ratio of 32.87. By comparing the accuracy-recall curve, the performance of this method is superior.