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      KCI등재 SCOPUS

      원격탐사활용을 위한 딥러닝기술 = Deep Learning for Remote Sensing Applications

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      https://www.riss.kr/link?id=A108426472

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      다국어 초록 (Multilingual Abstract)

      Recently, deep learning has become more important in remote sensing data processing. Huge amounts of data for artificial intelligence (AI) has been designed and built to develop new technologies for remote sensing, and AI models have been learned by t...

      Recently, deep learning has become more important in remote sensing data processing. Huge amounts of data for artificial intelligence (AI) has been designed and built to develop new technologies for remote sensing, and AI models have been learned by the AI training dataset. Artificial intelligence models have developed rapidly, and model accuracy is increasing accordingly. However, there are variations in the model accuracy depending on the person who trains the AI model. Eventually, experts who can train AI models well are required more and more. Moreover, the deep learning technique enables us to automate methods for remote sensing applications. Methods having the performance of less than about 60% in the past are now over 90% and entering about 100%. In this special issue, thirteen papers on how deep learning techniques are used for remote sensing applications will be introduced.

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