A novel framework for potato leaf disease detection using an efficient deep learning model
Rabbia Mahum(University of Engineering and Technology Taxila), Iskander Tlili(Majmaah University), Haris Munir(University of Engineering and Technology Taxila), Muhammad Saqlain(Pir Mehr Ali Shah Arid Agriculture University), Saipunidzam Mahamad(Universiti Teknologi Petronas), Muhammad Awais(Kyung Hee University), Falak Sher Khan(University of Sialkot), Zaib-Un-Nisa Mughal(University of Sindh)
Human and Ecological Risk Assessment An International Journal
April 19, 2022
Cited by 299
Related Papers
CCDF: Automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features
|Computers and Electronics in Agriculture|2018|236
Optimal sizing of photovoltaic systems based green hydrogen refueling stations case study Oman
|International Journal of Hydrogen Energy|2022|153
Advancements and Prospects of Machine Learning in Medical Diagnostics: Unveiling the Future of Diagnostic Precision
|Archives of Computational Methods in Engineering|2024|147
Potential prospects of supercritical CO2 power cycles for commercialisation: Applicability, research status, and advancement
|Renewable and Sustainable Energy Reviews|2022|130
AXM-Net: Implicit Cross-Modal Feature Alignment for Person Re-identification
|Proceedings of the AAAI Conference on Artificial Intelligence|2022|122