Zobrazeno 1 - 10
of 111
pro vyhledávání: '"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
Autor:
Liangliang Liu, Shixin Qiao, Jing Chang, Weiwei Ding, Cifu Xu, Jiamin Gu, Tong Sun, Hongbo Qiao
Publikováno v:
Heliyon, Vol 10, Iss 7, Pp e28264- (2024)
Maize is a globally important cereal crop, however, maize leaf disease is one of the most common and devastating diseases that afflict it. Artificial intelligence methods face challenges in identifying and classifying maize leaf diseases due to varia
Externí odkaz:
https://doaj.org/article/23cdaf745a35499680c5f56bf5b701b9
Publikováno v:
Data in Brief, Vol 52, Iss , Pp 109929- (2024)
The Plumbago Zeylanica (Chitrak) Leaf Image Dataset is a valuable resource for botanical studies, herbal medicine research, and environmental analyses. Comprising a total of 10,660 high-resolution leaf images, the dataset is meticulously categorized
Externí odkaz:
https://doaj.org/article/b2fa8213e0ac4ecfad6d24bd799aaac7
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:
Journal of Intelligent Systems, Vol 32, Iss 1, Pp 187-206 (2023)
With the rapid expansion in plant disease detection, there has been a progressive increase in the demand for more accurate systems. In this work, we propose a new method combining color information, edge information, and textural information to ident
Externí odkaz:
https://doaj.org/article/4a6aebcaa628484a8e4a0e39b5363459
Autor:
Pushpa B R, N. Shobha Rani
Publikováno v:
Data in Brief, Vol 49, Iss , Pp 109388- (2023)
Mobile-captured images of medicinal plants are widely used in various research investigations. Machine vision-based tasks such as the identification of plant species types for intelligent imaging device applications take a significant part in it. Bot
Externí odkaz:
https://doaj.org/article/2bc56759f08e47cf80f269648b777ad2
Akademický článek
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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
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
The detection of plant disease is of vital importance in practical agricultural production. It scrutinizes the plant's growth and health condition and guarantees the regular operation and harvest of the agricultural planting to proceed successfully.
Externí odkaz:
https://doaj.org/article/59cca8e9456943d9b4c8de78516bf752
Publikováno v:
IEEE Access, Vol 9, Pp 162590-162613 (2021)
In the practice of plant classification, the design of hand-crafted features is more dependent on the ability of computer vision experts to encode morphological characters that are predefined by botanists. However, the distinct features that each pla
Externí odkaz:
https://doaj.org/article/3245d3fb94b447dda6dc77ac47c4ed91