The master’s thesis of the student (Zahraa Essam Ibrahim) in the Department of Computer Engineering was discussed under the supervision of Dr. Nadia Adnan Shaltagh (on Sunday, January 21, 2024, in the discussion hall of the Computer Engineering Department) about her research titled:
“Slicing Multi-Spiking Intelligent Classification Method of Visual Terrain Applications”
After conducting the public discussion and listening to the student’s defense, the thesis was accepted. It was summarized as follows:
The thesis has proposed two types of supervised learning algorithms for spike neural networks with partial recurrence. These algorithms aim to classify six classes of terrain (hydrop, gravel, asphalt, grass, mud, and sand) based on vision data. The algorithms include a single-spike learning algorithm and a multi-spike learning algorithm. Simulation results indicate that the multi-spike learning algorithm outperforms the single-spike learning algorithm in terms of accuracy, precision, recall, and F1-score.
