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

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69

Publications

38

Academic Staff

1710

Students

159

Graduates

Faculty of Information Technology News

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بكالوريوس في تقنية المعلومات
Major هندسة البرمجيات

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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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Prof.Dr. HARMAIN MOHAMMED HARMAIN HARMAIN

الحرمين محمد الحرمين هو احد اعضاء هيئة التدريس بكلية تقنية المعلومات. يعمل الحرمين بجامعة طرابلس كـأستاذ في قسم هندسة البرمجيات منذ سنة 2014 وله العديد من المنشورات العلمية في مجال تخصصه...

Publications

Some of publications in Faculty of Information Technology

مجموعات الإختبار العربية ودورها في تطوير أداء محركات البحث العربية

يعتمد تطور البحث العلمي عادة على القياس. فبدون قياس لا يمكن معرفة مدى كفاءة أي نظام أو أداة مستحدثة. في هذه الورقة نعرض أدوات القياس التي يتم إستخدامها في تحديد كفاءة أنظمة إسترجاع المعلومات عموما و نركز على ما هو متوفر منها لقياس أنظمة إسترجاع النصوص العربية، ونبين مدى التطور التي أحدثه على مستوى إسترجاع النصوص العربية. تركز الورقة على عرض مجموعات الإختبار العربية المتوفرة حاليا, وتبرز القصور التي تعاني منه، وتظهر الحاجة الى وجود نجموعات اختبار عربية تتوافق مع واقع النصوص العربية الموجودة حاليا على شبكة المعلومات الدولية. كما نقوم بعرض مجموعة الإختبار التي قمنا بإعدادها لإختبار ظاهرة زيادة حجم النصوص العربية. ونبين أن زيادة الحجم في النصوص العربية يؤثر سلبا في مستوى آداء أنظمة الإسترجاع العربية. arabic 125 English 0
عبد السلام الفيتوري أحمد النويصري(10-2015)
Publisher's website

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%. arabic 9 English 69
Hassan Ali Hassan Ebrahem, Abdelhamid Elwaer, Marwa Solla, Fatima Ben Lashihar, Hala Shaari, Rudwan A. Husain(7-2021)
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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)
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