Faculty of Information Technology

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About Faculty of Information Technology

Faculty of Information Technology

The Faculty of Information Technology is one of the most recent faculties at the University of Tripoli, as it was established in pursuant to the former General People's Committee for Higher Education Decision No. 535 of 2007 regarding the creation of Information Technology Faculties in the main universities in Libya.

 

Upon its establishment, the Faculty consisted of three departments: Computer Networks Department, Computer Science Department and Software Engineering Department. It now includes five departments: Mobile Computing Department, Computer Network Department, Internet Technologies Department, Information Systems Department and Software Engineering Department.

 

The Faculty’s study system follows the open semester system by two (Fall and Spring) terms per year. The Faculty began to actually accept students and teach with the beginning of the Fall semester 2008. It grants a specialized (university) degree in information technology in any of the aforementioned disciplines. Obtaining the degree requires the successful completion of at least 135 credit hours. Arabic is the language of study in the college, and English may be also used alongside it. It takes eight semesters to graduate from the Faculty if Information Technology.

 

The Faculty aspires to open postgraduate programs in the departments of computer networks and software engineering in the near future.

Facts about Faculty of Information Technology

We are proud of what we offer to the world and the community

69

Publications

38

Academic Staff

1710

Students

159

Graduates

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Who works at the Faculty of Information Technology

Faculty of Information Technology has more than 38 academic staff members

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Dr. Trial Lecturer Lecturer Lecturer

عضو هيئة تدريس

Publications

Some of publications in Faculty of Information Technology

Applying Multiple Deep Learning Models for Antipersonal Landmines Recognition

Antipersonnel landmines represent a very serious hazard endangering the lives of many people living in armed conflict counties. The huge number of human lives lost due to this phenomenon has been a strong motivation for this research. Deep Learning (DL) is considered a very useful tool in object detection, image classification, face recognition and other computer vision activities. This paper focuses on DL for the problem of landmines recognition in order to identify its type based on shape features. This research work consists of several stages: gathering a new dataset of Anti-Personnel Mines (APMs) images for training and testing purposes, employing several augmentation strategies to boost the diversity of training data, applying four different Convolutional Neural Network (CNN) models namely VGG, ResNet, MiniGoogleNet and MobileNet, and evaluating their performances on APMs recognition. In conclusion, results indicate that MiniGoogleNet exceed all of other three models in recognizing APMs with the highest accuracy rate of 97%.
Hassan Ali Hassan Ebrahem, Abdelhamid Elwaer, Marwa Solla, Fatima Ben Lashihar, Hala Shaari, Rudwan A. Husain(7-2021)
Publisher's website

biometrics:standing throughout emerging technologies

Biometrics technologies have been around for quite some time and many have been deployed for different applications all around the world, ranging from small companies' time and attendance systems to access control systems for nuclear facilities. Biometrics offer a reliable solution for the establishment of the distinctiveness of identity based on "who an individual is", rather than what he or she knows or carries. Biometric Systems automatically verify a person's identity based on his/her anatomical and behavioral characteristics. Biometric traits represent a strong and undeviating link between a person and his/her identity, these traits cannot be easily lost or forgotten or faked, since biometric systems require the user to be present at the time of authentication. Some biometric systems are more reliable than others, yet they are neither secure nor accurate, all biometrics have their strengths and weaknesses. Although some of these systems have shown reliability and solidarity, work still has to be done to improve the quality of service they provide. Presented is the available standing biometric systems showing their strengths and weaknesses and also emerging technologies which may have great benefits for security applications in the near future.
Abdulmonam Omar Ahmed Alaswad(0-2008)
Publisher's website

Performance Analysis of Spoken Arabic Digits Recognition Techniques

A performance evaluation of sound recognition techniques in recognizing some spoken Arabic words, namely digits from zero to nine, is proposed. One of the main characteristics of all Arabic digits is polysyllabic words except for zero. The performance analysis is based on different features of phonetic isolated Arabic digits. The main aim of this paper is to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on three recognition features: the Yule-Walker spectrum features, the Walsh spectrum features, and the Mel frequency Cepstral coefficients (MFCC) features. The MFCC based recognition system achieves the best average correct recognition. On the other hand, the Yule-Walker based recognition system achieves the worst average correct recognition. arabic 7 English 60
A. Ganoun, I. Almerhag(6-2012)
Publisher's website