Deep Learning Based-Cotton Disease Recognition System

Muhammad Bilal, Yash Kumar, Akhtar HussainJalbani, Subhan khan Solangi
Additional contact information
Muhammad Bilal, Yash Kumar, Akhtar HussainJalbani, Subhan khan Solangi: Department of Computer Science Quaid-e-Awam University of Engineering Science and Technology, Nawabshah

International Journal of Innovations in Science & Technology, 2025, vol. 7, issue 6, 172-178

Abstract: Cotton is a vital cash crop in Sindh, Pakistan, playing a crucial role in the agricultural economy. However, diseases such as Cotton Leaf Curl Virus (CLCV), bacterial blight, and Fusariumwilt significantly reduce cotton yield, affecting farmers' livelihoods. Traditional disease identification methods are labor-intensive, error-prone, and inefficient, necessitating automated approaches for early and accurate detection. This research introduces a deep learning-based cotton disease recognition system, leveraging Convolutional Neural Networks (CNNs) with transfer learning to classify diseases. Experimental results demonstrate that our approach achieves high accuracy, offering an efficient, user-friendly, and scalable solution to promote sustainable agricultural practices in Pakistan.

Keywords: Deep Learning; CNN; cotton disease detection; Image Recognition; Agricultural Technology; Pattern Recognition (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journal.50sea.com/index.php/IJIST/article/view/1359/1891 (application/pdf)
https://journal.50sea.com/index.php/IJIST/article/view/1359 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:abq:ijist1:v:7:y:2025:i:6:p:172-178

Access Statistics for this article

International Journal of Innovations in Science & Technology is currently edited by Prof. Dr. Syed Amer Mahmood

More articles in International Journal of Innovations in Science & Technology from 50sea
Bibliographic data for series maintained by Iqra Nazeer ().