Research on the Construction Method and Key Technologies of Unexploded Submunition Image Dataset
With the rapid development and application of computer technology and machine vision technology,the exploration of unexploded submunition search technology based on"artificial intelligence+"model has received exten-sive attention.However,due to the danger of unexploded submunitions and the particularity of military applications,data set construction is a bottleneck problem that needs to be solved urgently.Based on this,the paper discusses the construction methods and processes of real physical image data sets and three-dimensional reconstruction data sets using physical images.It focuses on the analysis of the key technologies and their advantages and disadvantages in the con-struction process of the two data sets.A multi-camera is used to collect the target image and geographic coordinate in-formation,and then the deep learning algorithm is used to extract the target feature,generate the three-dimensional point cloud and fuse the three-dimensional image.The experimental results show that the three-dimensional data set constructed by this method can effectively solve the problem of insufficient data volume of the existing data set of unex-ploded submunitions.Finally,the future development direction of the data set construction method is prospected.
万方数据
维普
