Detection of cotton leaf curl disease’s susceptibility scale level based on deep learning

Detection of cotton leaf curl disease’s susceptibility scale level based on deep learning

Abstract Cotton, a crucial cash crop in Pakistan, faces persistent threats from diseases, notably the Cotton Leaf Curl Virus (CLCuV). Detecting these diseases accurately and early is vital for effective management. This paper offers a comprehensive account of the process involved in collecting, prep...

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Bibliographic Details
Main Authors: Rubaina Nazeer, Sajid Ali, Zhihua Hu, Ghulam Jillani Ansari, Muna Al-Razgan, Emad Mahrous Awwad, Yazeed Yasin Ghadi
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Cotton leaf curl disease virus (CLCuV)
Cotton leaf curl disease (CLCuD)
Dynamic weighted layering model (DWLM)
Convolutional neural network (CNN)
Online Access:https://doi.org/10.1186/s13677-023-00582-9

Internet

https://doi.org/10.1186/s13677-023-00582-9

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