Zobrazeno 1 - 7
of 7
pro vyhledávání: '"tomato leaf images"'
Publikováno v:
MethodsX, Vol 13, Iss , Pp 102844- (2024)
Plant diseases can spread rapidly, leading to significant crop losses if not detected early. By accurately identifying diseased plants, farmers can target treatment only to the affected areas, reducing the number of pesticides or fungicides needed an
Externí odkaz:
https://doaj.org/article/90c636014fc64f7dab5fe40ea092bd7e
Publikováno v:
Symmetry, Vol 16, Iss 6, p 723 (2024)
Target detection algorithms can greatly improve the efficiency of tomato leaf disease detection and play an important technical role in intelligent tomato cultivation. However, there are some challenges in the detection process, such as the diversity
Externí odkaz:
https://doaj.org/article/80a8d0f6aa89406ebed1748a5126824e
Publikováno v:
AgriEngineering, Vol 4, Iss 4, Pp 871-887 (2022)
Tomato leaves can have different diseases which can affect harvest performance. Therefore, accurate classification for the early detection of disease for treatment is very important. This article proposes one classification model, in which 16,010 tom
Externí odkaz:
https://doaj.org/article/a4666f6a115146a3aa3c8bcd08d145e0
Akademický článek
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Publikováno v:
AgriEngineering; Volume 4; Issue 4; Pages: 871-887
Tomato leaves can have different diseases which can affect harvest performance. Therefore, accurate classification for the early detection of disease for treatment is very important. This article proposes one classification model, in which 16,010 tom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a86c2f7222496b0c97a76f8750936d34
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Autor:
Al-Shamasneh AR; Department of Computer Science, College of Computer & Information Sciences, Prince Sultan University, Rafha Street, Riyadh 11586, Saudi Arabia., Ibrahim RW; Faculty of Engineering and Natural Sciences, Advanced Computing Lab, Istanbul Okan University, 34959, Türkiye.; Information and Communication Technology Research Group, Scientific Research Center, Alayen University, Nile Street, 64001, Dhi Qar, Iraq.
Publikováno v:
MethodsX [MethodsX] 2024 Jul 03; Vol. 13, pp. 102844. Date of Electronic Publication: 2024 Jul 03 (Print Publication: 2024).