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

Traditional haze pollution monitoring technology has low monitoring accuracy and poor integrity of collected images. In order to solve the above problems, a new haze pollution monitoring technology is researched based on deep learning. Accurately divide the place where it is generated through pollution data collection, integrate the acquired tracking information, control the possible conditions of haze pollution in the three-dimensional distribution space map, conduct machine flight tracking experiments many times, and monitor the haze pollution data according to different pollution project groups According to the concentration information of haze pollution data and the input data type of deep machine learning, the collected data is classified, and the data type is queried. At the same time, the thickness of the aerosol, the toxic sulfur dioxide and nitrogen dioxide substances in the haze pollution, and the area of interest are monitored. In order to verify the effectiveness of the technology, a comparative experiment is set up. The results show that the accuracy of the monitoring results of the haze pollution monitoring technology based on deep machine learning is 90%, and the average of the completeness of image collection is 82%, which has stronger monitoring capabilities.