The Informatics Institute for Postgraduate Studies at the University of Information Technology and Communications discussed the Master’s thesis submitted by graduate student Hanan Badri Salman, specializing in computer science, entitled: “A Deep Learning Model for Black Fungus Disease Identification Based on Salp Swarm Optimization”.

The thesis aimed to propose a diagnostic framework based on deep learning techniques for the early detection of black fungus infection, relying on Convolutional Neural Networks CNNs, while enhancing the model’s efficiency by employing meta-heuristic optimization algorithms, especially the negative swarm optimization algorithm.

The importance of the study stems from the aggressive nature of mycosis fungoides and the high mortality rates associated with it, especially with the delay in diagnosis, which calls for the development of accurate detection systems and mechanisms that contribute to accelerating the diagnosis process and raising the efficiency of health care.

After a thorough discussion by the chairman and members of the discussion committee, the student was awarded a Master’s degree in computer science with a grade of (Very Good).