The dielectric properties prediction of the vegetation depending on the moisture content using the deep neural network model-Reference-Cited by-同舟云学术

The dielectric properties prediction of the vegetation depending on the moisture content using the deep neural network model

Published:2020-11-20 Issue:1 Volume:31 Page:
ISSN:1096-4290
Container-title:International Journal of RF and Microwave Computer-Aided Engineering
language:en
Short-container-title:Int J RF Microw Comput Aided Eng

Author:

Metlek Sedat¹^ORCID,Kayaalp Kiyas²^ORCID,Basyigit Ibrahim Bahadir³^ORCID,Genc Abdullah⁴^ORCID,Dogan Habib⁵^ORCID

Affiliation:

1. Vocational School of Technical Sciences Mehmet Akif University Burdur Turkey

2. Uluborlu Selahattin Karasoy Vocational School Isparta University of Applied Science Isparta Turkey

3. Faculty of Technology, Department of Electrical and Electronics Engineering Isparta University of Applied Science Isparta Turkey

4. Faculty of Technology, Department of Mechatronics Engineering Isparta University of Applied Science Isparta Turkey

5. Department of Building Inspection Ministry of Environment and Urbanization, Isparta Provincial Directorate Isparta Turkey

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Link

Reference32 articles.

3. Estimation of moisture in maize leaf by measuring leaf dielectric constant;Afzal A;Int J Agric Biol,2008

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