Leveraging YOLO deep learning models to enhance plant disease identification
Al Jouf University · Information Technology University · +1 more institution
Abstract
Early automation in identifying plant diseases is crucial for the precise protection of crops. Plant diseases pose substantial risks to agriculture-dependent nations, often leading to notable crop losses and financial challenges, particularly in developing countries. Symptoms such as chlorosis, structural deformities, and wilting, characterize these diseases. However, early identification can be challenging due to symptoms similarity. Researchers using artificial intelligence (AI) for plant disease classification, challenges like data imbalance, symptom variability, real-time performance, and costly annotation hinder accuracy and adoption. This work introduced a novel approach using the You Only Look Once…
Citation impact
- FWCI
- 65.19
- Percentile
- 100%
- References
- 42
Authors
6- YAYousef AlhwaitiCorresponding
Al Jouf University
- MJMuhammad Jaleed Khan
Information Technology University, The University of Agriculture, Peshawar
- MAMuhammad Asim
The University of Agriculture, Peshawar, Information Technology University
- MHMuhammad Hameed Siddiqi
Al Jouf University
- MIMuhammad Ishaq
Information Technology University, The University of Agriculture, Peshawar
Topics & keywords
- Identification (biology)
- Computer science
- Deep learning
- Disease
- Artificial intelligence
- Data science
- Machine learning
- Computational biology
- Zero hunger