A graduate student from the Department of Computer Engineering at the University (Duha Hassan) qualified for and was admitted to the award of Master degree on 31-01-2019 at the conference hall of the Computer Engineering Department. The title of the thesis was: “the design and implementation of the object detection system using deep learning”

In this thesis, the researcher addressed the design of a system that provides an effective model with a simplified structure that uses less memory and processing power while maintaining good accuracy and speed. This system allows the computer to tell us directly that this image contains a certain object and where it is located inside the image. The proposed system depends on the extraction of the features of the object using (CNN) and then work on these characteristics or attributes to predict the dimensions that represent the location of the object and predict the type of object between the tested species and the use of another network containing more than one exit.

The system has been able to detect highly variable objects, lighting conditions and trend. The model (48.61 MAP) has provided a detailed discussion and insight into future work, which can be interesting for both academia and industry, especially in the field of learning and computer vision.

The discussion committee consisted of Prof. Dr. Emad H. Al-Husseini from the University of Technology / Computer Engineering Department as Chairman, Asst. Prof. Dr. Amjad J. Hamidi from the University of Technology / Department of Control and Systems Engineering as member, Asst. Prof. Dr. Muthana H. Hamad from Al- Mustansiriya University / College of Engineering / Computer Engineering Department as a Member, Asst. Prof. Dr. Bassem A. Jumaa and Dr. Saman H. Amin from the University of Technology / Computer Engineering Department as Members and Supervisors.