Zobrazeno 1 - 10
of 296
pro vyhledávání: '"plant leaf disease"'
Publikováno v:
IEEE Access, Vol 12, Pp 44573-44585 (2024)
In response to the challenge that traditional convolutional neural networks face in effectively capturing the posture and spatial relationships of plant disease lesions on leaves, leading to issues of low recognition accuracy and poor robustness, thi
Externí odkaz:
https://doaj.org/article/a6ca29751f024a70b5333f23b34966ac
Autor:
Md. Khairul Alam Mazumder, M. F. Mridha, Sultan Alfarhood, Mejdl Safran, Md. Abdullah-Al-Jubair, Dunren Che
Publikováno v:
Frontiers in Plant Science, Vol 14 (2024)
Leaf diseases are a global threat to crop production and food preservation. Detecting these diseases is crucial for effective management. We introduce LeafDoc-Net, a robust, lightweight transfer-learning architecture for accurately detecting leaf dis
Externí odkaz:
https://doaj.org/article/76b81aa19a1445acb3d59e36a2bd0566
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
The identification of plant leaf diseases is crucial in precision agriculture, playing a pivotal role in advancing the modernization of agriculture. Timely detection and diagnosis of leaf diseases for preventive measures significantly contribute to e
Externí odkaz:
https://doaj.org/article/cd6aabac810440b98c15e7f6b1717c88
Publikováno v:
Heliyon, Vol 10, Iss 9, Pp e29912- (2024)
Early detection of plant leaf diseases accurately and promptly is very crucial for safeguarding agricultural crop productivity and ensuring food security. During their life cycle, plant leaves get diseased because of multiple factors like bacteria, f
Externí odkaz:
https://doaj.org/article/9b0f492078c243e89447bdda6574c171
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Detecting plant leaf diseases accurately and promptly is essential for reducing economic consequences and maximizing crop yield. However, farmers’ dependence on conventional manual techniques presents a difficulty in accurately pinpointing particul
Externí odkaz:
https://doaj.org/article/3cedd06d668a40daa7b9a94dc45006db
Publikováno v:
Artificial Intelligence in Agriculture, Vol 9, Iss , Pp 22-35 (2023)
Although convolutional neural network (CNN) paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures, few studies have focused on the performance comparison of the applicability of these techniques i
Externí odkaz:
https://doaj.org/article/7a0447692a9e438e8a53b9075b3c7806
Autor:
Fizzah Arshad, Muhammad Mateen, Shaukat Hayat, Maryam Wardah, Zaid Al-Huda, Yeong Hyeon Gu, Mugahed A. Al-antari
Publikováno v:
Alexandria Engineering Journal, Vol 78, Iss , Pp 406-418 (2023)
Agricultural productivity plays a vital role in global economic development and growth. When crops are affected by diseases, it adversely impacts a nation’s economic resources and agricultural output. Early detection of crop diseases can minimize l
Externí odkaz:
https://doaj.org/article/4b5902aab0b242cbb38c1ffa83e751cd
Autor:
Samia Allaoua Chelloug, Reem Alkanhel, Mohammed Saleh Ali Muthanna, Ahmed Aziz, Ammar Muthanna
Publikováno v:
IEEE Access, Vol 11, Pp 86770-86789 (2023)
Agriculture plays the vigorous role in economy as well as it is contemplated to be the mainstay of economic system in emerging countries. Furthermore, it influences the society in huge ways including ancillary livelihoods, anyhow occurring of plant d
Externí odkaz:
https://doaj.org/article/1cf2650140ad4fcca3886034ddc830ed
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Plants are widely grown around the world and have high economic benefits. plant leaf diseases not only negatively affect the healthy growth and development of plants, but also have a negative impact on the environment. While traditional manual method
Externí odkaz:
https://doaj.org/article/83aee69e8c654ee4815440e8f124a506
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