The master's thesis for the student (Dina Mahdi Abdul-Hussein) was discussed with a major in (Computer Engineering) on Tuesday 4/10/2022 at the discussion room (Hall No. 9). The thesis title is “Object Features and Behavior Analysis using Deep Learning” This discussion committee consisted of:

1- Prof. Dr. Ashwaq Talib Hashem / Chairman

2- Asst. Prof. Dr. Intisar Abdul Majeed Al-Sayed / Member

3- Asst. Prof. Dr. Ahmed Raouf Nasser / Member

4- Asst. Prof. Dr. Laith Jassim Saud / Member and Supervisor

The exponential increase in the use of image processing and artificial intelligence in a very large number of applications in many fields makes it a stimulating field for education, business and research. Object detection and analysis is needed in most of these applications. This work is specifically concerned with the human face as an object. For years and still, different face detection methods with different approaches have been competing for better efficiency. Feature-based and image-based methods are the two main methods among these methods. In this work: A relatively extensive review of the methods used in face detection has been undertaken with an overview of their capabilities and limitations. • Two important face detection and analysis methods, one that uses Viola Jones' idea and belongs to the feature-based approach and the other is deep learning on CNN and belongs to the image-based approach, are implemented and analyzed, considering their structure, method of training and work, factors affecting their work, capabilities, limitations, and suitability for detection and analysis. • Ensures working with training as well as testing algorithms Working with algorithms included training as well as testing. The work is carried out on computing platforms (personal computers) with different capabilities, and as a programming environment, PyCharm is used as an integrated development environment with Python as a programming language as well as various libraries that support the construction of algorithms and support the best use of practical computing units. The data sets used in training or tests are taken from internet sources. When choosing the method to use for an application, it is important to consider, among many things, the purposes of the application in terms of accuracy, time, resources, and ability to use the GPU. The door is still open to effective new methods, as well as improving the efficiency of already existing methods. On this occasion, we congratulate the student (Dina Mahdi Abdul-Hussein) and wish her continued success.