Researcher Image
شهلاء طالب عبد الوهاب - Shahlaa Mashhadani
PhD - lecturer
College of Education for Pure Sciences (Ibn Al-Haitham) , Deparment of Computer Science
[email protected]
Qualifications

2001 B.Sc. in Computer Science/ Ibn-Al-Haitham Education College/University of Baghdad/Baghdad/Iraq. 2005 M.Sc. in Computer Science/ College of Science/University of Baghdad/ Baghdad/Iraq. 2019 Ph.D. in Computer Science/ University of Plymouth /Plymouth/United Kingdom.

Responsibility

Baghdad University/College of Education/ Ibn Al-Haitham/Baghdad/ IRAQ. AUGUST 2001- APRIL 2015 (ACADEMIC LECTURER) Ph.D. student at Plymouth University/United Kingdom.

Baghdad University/College of Education/ Ibn Al-Haitham/Baghdad/ IRAQ. APRIL 2015- OCT.2019

JAN. 2020 – TILL NOW (ACADEMIC LECTURER)

Research Interests
  1. Digital Forensics.
  2. Multimedia Forensics Analysis
  3. Image processing.
  4. Image based retrieval.
  5. Information security.
  6. DataBases
Publication Date
Tue Jan 01 2019
Journal Name
Proceedings Of The 5th International Conference On Information Systems Security And Privacy
Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion
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Scopus (1)
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Publication Date
Fri Dec 01 2017
Journal Name
2017 12th International Conference For Internet Technology And Secured Transactions (icitst)
A novel multimedia-forensic analysis tool (M-FAT)
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Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Fri Mar 30 2018
Journal Name
International Journal Of Multimedia And Image Processing
The Design of a Multimedia-Forensic Analysis Tool (M-FAT)
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Digital forensics has become a fundamental requirement for law enforcement due to the growing volume of cyber and computer-assisted crime. Whilst existing commercial tools have traditionally focused upon string-based analyses (e.g., regular expressions, keywords), less effort has been placed towards the development of multimedia-based analyses. Within the research community, more focus has been attributed to the analysis of multimedia content; they tend to focus upon highly specialised specific scenarios such as tattoo identification, number plate recognition, suspect face recognition and manual annotation of images. Given the ever-increasing volume of multimedia content, it is essential that a holistic Multimedia-Forensic Analysis Tool (M-

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Crossref (1)
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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Neutrosophic Science
A New Paradigm for Decision Making under Uncertainty in Signature Forensics Applications based on Neutrosophic Rule Engine
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One of the most popular and legally recognized behavioral biometrics is the individual's signature, which is used for verification and identification in many different industries, including business, law, and finance. The purpose of the signature verification method is to distinguish genuine from forged signatures, a task complicated by cultural and personal variances. Analysis, comparison, and evaluation of handwriting features are performed in forensic handwriting analysis to establish whether or not the writing was produced by a known writer. In contrast to other languages, Arabic makes use of diacritics, ligatures, and overlaps that are unique to it. Due to the absence of dynamic information in the writing of Arabic signatures,

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Scopus Crossref
Publication Date
Thu Oct 31 2024
Journal Name
Intelligent Automation And Soft Computing
Fusion of Type-2 Neutrosophic Similarity Measure in Signatures Verification Systems: A New Forensic Document Analysis Paradigm
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Signature verification involves vague situations in which a signature could resemble many reference samples or might differ because of handwriting variances. By presenting the features and similarity score of signatures from the matching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy, a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertainties and ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values, which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1 neutrosophic representation is also unable to adjust to various

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Crossref
Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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