An advanced deep learning models-based plant disease detection: A review of recent research
Sarhad University of Science and Information Technology · CECOS University · +10 more institutions
Abstract
Plants play a crucial role in supplying food globally. Various environmental factors lead to plant diseases which results in significant production losses. However, manual detection of plant diseases is a time-consuming and error-prone process. It can be an unreliable method of identifying and preventing the spread of plant diseases. Adopting advanced technologies such as Machine Learning (ML) and Deep Learning (DL) can help to overcome these challenges by enabling early identification of plant diseases. In this paper, the recent advancements in the use of ML and DL techniques for the identification of plant diseases are explored. The research focuses on publications between 2015 and 2022, and the experiments…
Citation impact
- FWCI
- 164.64
- Percentile
- 100%
- References
- 101
Authors
9- MSMuhammad Shoaib
Sarhad University of Science and Information Technology, CECOS University
- BSBabar Shah
Zayed University
- SEShaker El–Sappagh
Suez University, Benha University, Galala University
- AAAkhtar Ali
Center of Plant Systems Biology and Biotechnology
- AUAsad Ullah
Sarhad University of Science and Information Technology
Topics & keywords
- Identification (biology)
- Computer science
- Process (computing)
- Plant disease
- Risk analysis (engineering)
- Quality (philosophy)
- Artificial intelligence
- Data science