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http://dx.doi.org/10.24225/kjai.2021.9.2.7

Implementation of CNN-based Masking Algorithm for Post Processing of Aerial Image  

CHOI, Eunsoo (Smart Geospatial Research Center, ALLFORLAND Co.Ltd)
QUAN, Zhixuan (Department of Alternative Medicine, Kwangju Women's University)
JUNG, Sangwoo (ALLFORLAND Co.Ltd)
Publication Information
Korean Journal of Artificial Intelligence / v.9, no.2, 2021 , pp. 7-14 More about this Journal
Abstract
Purpose: To solve urban problems, empirical research is being actively conducted to implement a smart city based on various ICT technologies, and digital twin technology is needed to effectively implement a smart city. A digital twin is essential for the realization of a smart city. A digital twin is a virtual environment that intuitively visualizes multidimensional data in the real world based on 3D. Digital twin is implemented on the premise of the convergence of GIS and BIM, and in particular, a lot of time is invested in data pre-processing and labeling in the data construction process. In digital twin, data quality is prioritized for consistency with reality, but there is a limit to data inspection with the naked eye. Therefore, in order to improve the required time and quality of digital twin construction, it was attempted to detect a building using Mask R-CNN, a deep learning-based masking algorithm for aerial images. If the results of this study are advanced and used to build digital twin data, it is thought that a high-quality smart city can be realized.
Keywords
Aerial Image; Mask R-CNN; CNN; Digital Twin; Smart City;
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