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- W3205017083 abstract "The United States Department of Defense (DoD) does not have an automated way in which they create Gridded Reference Graphics (GRGs). The current process is time intensive and requires expertise in numerous domains. We developed a two-step method using python scripting and machine learning to semi-automate the GRG development process. The two steps include 1) analyzing satellite imagery of the site to detect buildings and roads, 2) categorize and label buildings, and roads to meet DoD standards. The proposed methodology requires minimal expertise and enables the user to control various aspects of the workflow. Results revealed a 90% reduction in processing time when compared to the conventional approach." @default.
- W3205017083 created "2021-10-25" @default.
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- W3205017083 date "2021-07-11" @default.
- W3205017083 modified "2023-09-26" @default.
- W3205017083 title "Development of Gridded Reference Graphics Using Machine Learning and a Customized Geoprocessing Workflow" @default.
- W3205017083 doi "https://doi.org/10.1109/igarss47720.2021.9554413" @default.
- W3205017083 hasPublicationYear "2021" @default.
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