Master’s thesis in the Department of Computer Science discusses plant disease classification based on machine learning and metaheuristic optimization algorithm

The Department of Computer Science discussed the master’s thesis entitled Plant Disease Classification Based On Machine Learning And Metaheuristic Optimization for the master’s student (Hamsa Imad Mahmoud) Computer Science / Software on Tuesday 12/24/2024 at the hall of the late Dr. Imad Kazem.

The main objective of the thesis is to diagnose plant diseases by identifying the type of disease that affected the plant leaf early before the spread of the disease and the loss of agricultural crops, which affects the sustainability of plants and food in the world. The results showed that the best accuracy was obtained when using the proposed hybrid method SSGWO in selecting the best features. When the system was applied to real images taken from the farm, it gave very good results in diagnosing leaf diseases. The discussion committee consisted of Prof. Dr. Aliaa Karim Abdul Hassan as chairperson and members of Prof. Dr. Noha Jamil Ibrahim, Prof. Dr. Reem Razzaq Abdulhussain, Prof. Dr. Yusra Hussein Ali as member and supervisor, and Prof. Dr. Tariq Ahmed Rashid as member and supervisor.