Map Detection using Deep LearningMap Detection using Deep Learning
- Other Titles
- Map Detection using Deep Learning
- Authors
- 오병우
- Issue Date
- 2020
- Publisher
- 한국정보기술학회
- Keywords
- geographic map; object detection; deep learning; Faster R-CNN
- Citation
- 한국정보기술학회 영문논문지, v.10, no.2, pp.61 - 72
- Journal Title
- 한국정보기술학회 영문논문지
- Volume
- 10
- Number
- 2
- Start Page
- 61
- End Page
- 72
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/18543
- ISSN
- 2234-1072
- Abstract
- Recently, researches that are using deep learning technology in various fields are being conducted. The fields include geographic map processing. In this paper, I propose a method to infer where the map area included in the image is. The proposed method generates and learns images including a map, detects map areas from input images, extracts character strings belonging to those map areas, and converts the extracted character strings into coordinates through geocoding to infer the coordinates of the input image. Faster R-CNN was used for learning and map detection. In the experiment, the difference between the center coordinate of the map on the test image and the center coordinate of the detected map is calculated. The median value of the results of the experiment is 0.00158 for longitude and 0.00090 for latitude. In terms of distance, the difference is 141m in the east-west direction and 100m in the north-south direction.
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Collections - Department of Computer Engineering > 1. Journal Articles
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