Special Issue Review: Artificial Intelligence and Machine Learning Applications in Remote Sensing

被引:10
|
作者
Chen, Ying-Nong [1 ,2 ]
Fan, Kuo-Chin [2 ]
Chang, Yang-Lang [3 ]
Moriyama, Toshifumi [4 ]
机构
[1] Natl Cent Univ, Ctr Space & Remote Sensing Res, 300 Jhongda Rd, Taoyuan City 32001, Taiwan
[2] Natl Cent Univ, Dept Comp Sci & Informat Engn, 300 Jhongda Rd, Taoyuan City 32001, Taiwan
[3] Natl Taipei Univ Technol, Dept Elect Engn, Taipei 10608, Taiwan
[4] Nagasaki Univ, Grad Sch Engn, 1-14 Bunkyo Machi, Nagasaki 8528521, Japan
关键词
artificial intelligence; machine learning; deep learning; remote sensing; CLASSIFICATION;
D O I
10.3390/rs15030569
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Remote sensing is used in an increasingly wide range of applications. Models and methodologies based on artificial intelligence (AI) are commonly used to increase the performance of remote sensing technologies. Deep learning (DL) models are the most widely researched AI-based models because of their effectiveness and high performance. Therefore, we organized a Special Issue on remote sensing titled "Artificial Intelligence and Machine Learning Applications in Remote Sensing." In this paper, we review nine articles included in this Special Issue, most of which report studies based on satellite data and DL, reflecting the most prevalent trends in remote sensing research, as well as how DL architecture and the functioning of DL models can be analyzed and explained is a hot topic in AI research. DL methods can outperform conventional machine learning methods in remote sensing; however, DL remains a black box and understanding the details of the mechanisms through which DL models make decisions is difficult. Therefore, researchers must continue to investigate how explainable DL methods for use in the field of remote sensing can be developed.
引用
收藏
页数:10
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