A master's thesis in the Department of Computer Science discusses the classification of unusual driving behavior using the Dense Net network

Monday, 16 October 2023 21:14

A master's thesis in the Department of Computer Science discusses the classification of unusual driving behavior using the Dense Net network

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The Computer Science Department discussed the tagged master's thesis Abnormal driving behavior classification based on adaptive Dense Net For master’s student Aisha Iyad Ahmed/Computer Science/Software in the discussion room in the Computer Science Annex building. The thesis aims to use advanced deep learning techniques, especially Dense Net, to create an adaptive model that can detect abnormal driving behaviors and classify them accurately, leading to safer roads for everyone and reducing traffic accidents. The discussion committee consisted of Prof. Dr. Bilal Ismail Khalil as chairman, Prof. Ikhlas Faleh Nasser as members, Prof. Azra Jassim Muhammad, and Prof. Mathil Imad Al-Din as member and supervisor.

Source: Department's Media

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