국내학회지 논문 리뷰를 통한 원격탐사 분야 딥러닝 연구 동향 분석

Translated title of the contribution: Analysis of Deep Learning Research Trends Applied to Remote Sensing through Paper Review of Korean Domestic Journals

Changhui Lee, Yerin Yun, Saejung Bae, Yang Dam Eo, Changjae Kim, Sangho Shin, Soyoung Park, Youkyung Han

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations

Abstract

In the field of remote sensing in Korea, starting in 2017, deep learning has begun to show efficient research results compared to existing research methods. Currently, research is being conducted to apply deep learning in almost all fields of remote sensing, from image preprocessing to applications. To analyze the research trend of deep learning applied to the remote sensing field, Korean domestic journal papers, published until October 2021, related to deep learning applied to the remote sensing field were collected. Based on the collected 60 papers, research trend analysis was performed while focusing on deep learning network purpose, remote sensing application field, and remote sensing image acquisition platform. In addition, open source data that can be effectively used to build training data for performing deep learning were summarized in the paper. Through this study, we presented the problems that need to be solved in order for deep learning to be established in the remote sensing field. Moreover, we intended to provide help in finding research directions for researchers to apply deep learning technology into the remote sensing field in the future.

Translated title of the contributionAnalysis of Deep Learning Research Trends Applied to Remote Sensing through Paper Review of Korean Domestic Journals
Original languageKorean
Pages (from-to)437-456
Number of pages20
JournalJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
Volume39
Issue number6
DOIs
StatePublished - 2021

Keywords

  • Analysis of research trend
  • Deep learning
  • Image acquisition platform
  • Open source data
  • Remote sensing

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