Dr. Taqwa Al-Hadidi Showcases Innovative Traffic and Road Safety Solutions at IEEE International Conference

Dr. Taqwa Al-Hadidi from the Faculty of Engineering participated in the Third IEEE International Conference on Computing and Machine Learning. She presented two research papers, one titled "Automatic Detection and Classification of Road Pavement Cracks Using Deep Learning Tools" and another titled "Automatic Classification of Traffic Sign Types Using Deep Learning and Transfer Learning Techniques." In her presentations, Dr. Al-Hadidi showcased an algorithm for the automatic detection and identification of various road defects using deep learning techniques. This work included the detection and identification of different types of defects. In her second research paper, she introduced a new algorithm for recognizing and classifying different types of traffic signs. This development involved modifying the classification layer and integrating multiple types of classifications. The proposed model achieved an efficiency and effectiveness of 99.17%, particularly notable for its ability to function under challenging conditions such as low lighting and adverse weather.