JIPS (한국정보처리학회)
Current Result Document : 2 / 2
| 한글제목(Korean Title) |
A Survey of Deep Learning in Agriculture: Techniques and Their Applications |
| 영문제목(English Title) |
A Survey of Deep Learning in Agriculture: Techniques and Their Applications |
| 저자(Author) |
Chengjuan Ren
Dae-Kyoo Kim
Dongwon Jeong
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| 원문수록처(Citation) |
VOL 16 NO. 05 PP. 1015 ~ 1033 (2020. 10) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
With promising results and enormous capability, deep learning technology has attracted more and more attention to both theoretical research and applications for a variety of image processing and computer vision tasks. In this paper, we investigate 32 research contributions that apply deep learning techniques to the agriculture domain. Different types of deep neural network architectures in agriculture are surveyed and the current state-of-the-art methods are summarized. This paper ends with a discussion of the advantages and disadvantages of deep learning and future research topics. The survey shows that deep learning-based research has superior performance in terms of accuracy, which is beyond the standard machine learning techniques nowadays.
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| 키워드(Keyword) |
Deep Learning
Agriculture
State-of-the-Art
Survey
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| 파일첨부 |
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