Anbar Logo       A Proposed Hybrid Biometric Technique for Patterns Distinguishing       Anbar Logo       To the honorable researchers       Anbar Logo       A team from the College of Computer Science and Information Technology - University of Anbar represents Iraq in the Huawei International Competition qualifiers       Anbar Logo       Pilot competitive examination for applicants to graduate studies for the academic year (2022-2023)       Anbar Logo       Academic article by the teacher, Dr. Muhammad salah Ibrahim

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 Conducting a pilot competitive examination for applicants for graduate studies in the College of Computer Science and Information Technology / University of Anbar for the academic year 2022-2023

Pilot competitive examination for applicants to graduate studies for the academic year (2022-2023)

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 Common Gabor Features for Image Watermarking Identification

Academic article by Assistant Professor Dr. Ismail Taha AhmedCommon Gabor Features for Image Watermarking Identification Assist Prof Dr. Ismail Taha Ahmed Abstract Image watermarking is one of many methods for preventing unauthorized alterations to digital images. The major goal of the research is to find and identify photos that include a watermark, regardless of the method used to add the watermark or the shape of the watermark. As a result, this study advocated using the best Gabor features and classifiers to improve the accuracy of image watermarking identification. As classifiers, discriminant analysis (DA) and random forests are used. The DA and random forest use mean squared energy feature, mean amplitude feature, and combined feature vector as inputs for classification. The performance of the classifiers is evaluated using a variety of feature sets, and the best results are achieved. In order to assess the performance of the proposed method, we use a public database. VOC2008 is a public database that we use. The findings reveal that our proposed method’s DA classifier with integrated features had the greatest TPR of 93.71 and the lowest FNR of 6.29. This shows that the performance outcomes of the proposed approach are consistent. The proposed method has the advantages of being able to find images with the watermark in any database and not requiring a specific type or algorithm for embedding the watermark. Keywords watermarking identification; Gabor feature; discriminant analysis (DA) classifier; Random_forest classifier

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The start of the exams for the first stage of the first semester in the Faculty of Computer Science and Information Technology for the academic year 2021/2022

Final exams - first stage

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Scientific discussion for a master's student (Hamsa Mohamed Ahmed)

Discussion of a master's thesis in the College of Computer Science and Information Technology

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completing the evidence that would inform students, researchers

Curriculum guide at the University of Anbar for the year 2021.

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A Proposed Hybrid Biometric Technique for Patterns Distinguishing

 Academic article for teaching in the Department of Computer Networks Systems (Lecturer.Eman Turki)

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Academic article by the teacher, Dr. Muhammad salah Ibrahim

 Natural Language Processing


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Academic article by the Dr. Baraa Tariq Shawka

A Steganalysis Classification Algorithm Based on Distinctive Texture Features

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Academic article by the teacher, Dr. Baraa Tariq Shawka

Common Gabor Features for Image Watermarking Identification

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Academic article by Assistant Professor Dr. Khaled Shaker

Bacteria Swarm Optimization Approach for Enrolment-Based Course Timetabling Problems

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Academic article by LEC : SAIF El-Din Mahmoud Negm

Recruitment Internet Of Things For Medical Condition Assessment: Electrocardiogram Signal Surveillance

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