Ali Sami Azeez Al-Itbi

@mtu.edu.iq

Informatics Department
Middle Technical University



                       

https://researchid.co/ali26sami

EDUCATION

Bs.c. Computer science 2007.
M.Sc. Computer 2014.
PhD. Computer Science student.

RESEARCH INTERESTS

NLP, Deep Learning, Machine Learning.

7

Scopus Publications

23

Scholar Citations

3

Scholar h-index

Scopus Publications

  • An Intelligent Iris Recognition Technique
    Salam Muhsin Arnoos, Ali Mohammed Sahan, Alla Hussein Omran Ansaf, and Ali Sami Al-Itbi
    Springer Nature Singapore

  • Human identification using finger knuckle features
    Ali Sahan Sahan, Nisreen Jabr, Ahmed Bahaaulddin, and Ali Al-Itb
    International Journal of Advances in Soft Computing and its Applications Alzaytoonah University of Jordan
    Abstract Many studies refer that the figure knuckle comprises unique features. Therefore, it can be utilized in a biometric system to distinguishing between the peoples. In this paper, a combined global and local features technique has been proposed based on two descriptors, namely: Chebyshev Fourier moments (CHFMs) and Scale Invariant Feature Transform (SIFT) descriptors. The CHFMs descriptor is used to gaining the global features, while the scale invariant feature transform descriptor is utilized to extract local features. Each one of these descriptors has its advantages; therefore, combining them together leads to produce distinct features. Many experiments have been carried out using IIT-Delhi knuckle database to assess the accuracy of the proposed approach. The analysis of the results of these extensive experiments implies that the suggested technique has gained 98% accuracy rate. Furthermore, the robustness against the noise has been evaluated. The results of these experiments lead to concluding that the proposed technique is robust against the noise variation. Keywords: finger knuckle, biometric system, Chebyshev Fourier moments, scale invariant feature transform, IIT-Delhi knuckle database.

  • X-ray covid-19 detection based on scatterwavelet transform and dense deep neural network
    Ali Sami Al-Itbi, Ahmed Bahaaulddin A. Alwahhab, and Ali Mohammed Sahan
    Computer Systems Science and Engineering Computers, Materials and Continua (Tech Science Press)
    Notwithstanding the discovery of vaccines for Covid-19, the virus's rapid spread continues due to the limited availability of vaccines, especially in poor and emerging countries. Therefore, the key issues in the present COVID-19 pandemic are the early identification of COVID-19, the cautious separation of infected cases at the lowest cost and curing the disease in the early stages. For that reason, the methodology adopted for this study is imaging tools, particularly computed tomography, which have been critical in diagnosing and treating the disease. A new method for detecting Covid-19 in X-rays and CT images has been presented based on the Scatter Wavelet Transform and Dense Deep Neural Network. The Scatter Wavelet Transform has been employed as a feature extractor, while the Dense Deep Neural Network is utilized as a binary classifier. An extensive experiment was carried out to evaluate the accuracy of the proposed method over three datasets: IEEE 80200, Kaggle, and Covid-19 X-ray image data Sets. The dataset used in the experimental part consists of 14142. The numbers of training and testing images are 8290 and 2810, respectively. The analysis of the result refers that the proposed methods achieved high accuracy of 98%. The proposed model results show an excellent outcome compared to other methods in the same domain, such as (DeTraC) CNN, which achieved only 93.1%, CNN, which achieved 94%, and stacked Multi-Resolution CovXNet, which achieved 97.4%. The accuracy of CapsNet reached 97.24%.

  • An intelligent ear recognition technique


  • COVID-19 detection based on deep learning and artificial bee colony
    Ali Mohammed Sahan, Ali Sami Al-Itbi, and Jawad Sami Hameed
    Periodicals of Engineering and Natural Sciences International University of Sarajevo

  • The Fusion of Local and Global Descriptors in Face Recognition Application
    Ali Mohammed Sahan and Ali Sami Al-Itbi
    Lecture Notes in Electrical Engineering Springer Singapore

  • Rotation invariant face recognition using jacobi –fourier moments


RECENT SCHOLAR PUBLICATIONS

  • Rotation Invariant Technique for Sign Language Recognition
    MTD Al-Obaidi, AM Sahan, AS Al-Itbi
    InfoTech Spectrum: Iraqi Journal of Data Science 1 (1), 16-27 2024

  • An intelligent iris recognition technique
    SM Arnoos, AM Sahan, AHO Ansaf, AS Al-Itbi
    Next Generation of Internet of Things: Proceedings of ICNGIoT 2022, 207-217 2022

  • Human identification using finger knuckle features.
    AM Sahan, NAA Jabr, ASA Al-Itbi
    International Journal of Advances in Soft Computing & Its Applications 14 (1) 2022

  • X-Ray Covid-19 Detection Based on Scatter Wavelet Transform and Dense Deep Neural Network
    AMS Ali Sami Al-Itbi, Ahmed Bahaaulddin A. Alwahhab
    Computer Systems Science and Engineering 41 (3), 1255–1271 2022

  • An Intelligent Ear Recognition Technique.
    YA Hussein, ALI Sahan, ASA Al-Itbi
    International Journal of Advances in Soft Computing & Its Applications 13 (3) 2021

  • COVID-19 detection based on deep learning and artificial bee colony
    AM Sahan, AS Al-Itbi, JS Hameed
    Periodicals of Engineering and Natural Sciences 9 (1), 29-36 2021

  • The fusion of local and global descriptors in face recognition application
    AM Sahan, AS Al-Itbi
    International Conference on Advanced Communication and Computational 2019

  • Rotation invariant face recognition using jacobi –fourier moments
    AM Sahan, AS Azeez, MF Ibrahim
    Journal of Theoretical and Applied Information Technology 97 (5), 1444-1456 2019

  • PROPOSED AN ARCHITECTURE FOR BOTTELNECK NETWORK
    MA Jassim, AS Al-Itbi
    journal of the college of basic education 24 (100/علمي) 2018

  • Arabic (Indian) Numeral Handwritten Recognition Using Angular Radial Transform
    AS Azeez, AM Sahan
    Diyala Journal for Pure Sciences 13 (2), 48-64 2017

  • Rotation Invariant Face Recognition Using Radial Harmonic Fourier Moments
    AS Azeez
    Journal of The College of Basic Education 23 (99), 87-98 2017

  • Public Auditing In Secure Cloud Storage
    AS Azeez
    International Journal of Computer Engineering & Technology 5 (3) 2014

MOST CITED SCHOLAR PUBLICATIONS

  • X-Ray Covid-19 Detection Based on Scatter Wavelet Transform and Dense Deep Neural Network
    AMS Ali Sami Al-Itbi, Ahmed Bahaaulddin A. Alwahhab
    Computer Systems Science and Engineering 41 (3), 1255–1271 2022
    Citations: 6

  • COVID-19 detection based on deep learning and artificial bee colony
    AM Sahan, AS Al-Itbi, JS Hameed
    Periodicals of Engineering and Natural Sciences 9 (1), 29-36 2021
    Citations: 6

  • The fusion of local and global descriptors in face recognition application
    AM Sahan, AS Al-Itbi
    International Conference on Advanced Communication and Computational 2019
    Citations: 4

  • Rotation Invariant Face Recognition Using Radial Harmonic Fourier Moments
    AS Azeez
    Journal of The College of Basic Education 23 (99), 87-98 2017
    Citations: 2

  • Public Auditing In Secure Cloud Storage
    AS Azeez
    International Journal of Computer Engineering & Technology 5 (3) 2014
    Citations: 2

  • An intelligent iris recognition technique
    SM Arnoos, AM Sahan, AHO Ansaf, AS Al-Itbi
    Next Generation of Internet of Things: Proceedings of ICNGIoT 2022, 207-217 2022
    Citations: 1

  • Human identification using finger knuckle features.
    AM Sahan, NAA Jabr, ASA Al-Itbi
    International Journal of Advances in Soft Computing & Its Applications 14 (1) 2022
    Citations: 1

  • An Intelligent Ear Recognition Technique.
    YA Hussein, ALI Sahan, ASA Al-Itbi
    International Journal of Advances in Soft Computing & Its Applications 13 (3) 2021
    Citations: 1