Ahmad S. Lateef

@uomustansiriyah.edu.iq

Department of Physics/ College of Science
Mustansiriyah University

Ahmad S. Lateef


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https://researchid.co/a97s21m

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Vision and Pattern Recognition, Artificial Intelligence, Nuclear and High Energy Physics, Computer Science Applications
3

Scopus Publications

35

Scholar Citations

3

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition
    Ahmad S. Lateef, Mohammed Y. Kamil
    An Najah University Journal for Research A Natural Sciences, 2025
    Objective: Recording attendance is a critical process in academic institutions due to its significant impact on student performance and engagement. Current methods for recording attendance are often time-consuming and labour-intensive for lecturers and administrative staff, necessitating the development of more efficient and flexible solutions. While various automated attendance systems have been proposed, they often encounter challenges related to cost, implementation complexity, or reliability, hindering widespread adoption in educational settings. Method: This paper introduces a novel approach to automating attendance registration using face recognition technology. Our method integrates multiple feature extraction algorithms within a user-friendly graphical interface, specifically designed in English to enhance usability. By using existing security cameras commonly found in academic institutions, our approach addresses both cost and time inefficiencies. The attendance registration process involves capturing a video of the classroom, which is then processed to identify and log student attendance in a CSV file. A significant aspect of our study is using a comprehensive dataset comprising 2,170 images collected from 31 students at Mustansiriyah University. This extensive dataset enhances the robustness and reliability of our system, providing a diverse range of facial expressions, angles, and lighting conditions that improve the accuracy and generalizability of our model. Result: The system demonstrated accuracy of up to 100%, with deep learning algorithms outperforming machine learning methods. Conclusion: These promising results suggest that face recognition technology can effectively streamline and automate attendance tracking, offering a viable solution for educational institutions seeking to improve operational efficiency and accuracy
  • Face Recognition-Based Automatic Attendance System in a Smart Classroom
    Ahmad Lateef, Mohammed Kamil
    Iraqi Journal for Electrical and Electronic Engineering, 2024
    The smart classroom is a fully automated classroom where repetitive tasks, including attendance registration, are automatically performed. Due to recent advances in artificial intelligence, traditional attendance registration methods have become challenging. These methods require significant time and effort to complete the process. Therefore, researchers have sought alternative ways to accomplish attendance registration. These methods include identification cards, radio frequency, or biometric systems. However, all of these methods have faced challenges in safety, accuracy, effort, time, and cost. The development of digital image processing techniques, specifically face recognition technology, has enabled automated attendance registration. Face recognition technology is considered the most suitable for this process due to its ability to recognize multiple faces simultaneously. This study developed an integrated attendance registration system based on the YOLOv7 algorithm, which extracts features and recognizes students’ faces using a specially collected database of 31 students from Mustansiriyah University. A comparative study was conducted by applying the YOLOv7 algorithm, a machine learning algorithm, and a combined machine learning and deep learning algorithm. The proposed method achieved an accuracy of up to 100%. A comparison with previous studies demonstrated that the proposed method is promising and reliable for automating attendance registration.
  • Facial Recognition Technology-Based Attendance Management System Application in Smart Classroom
    Ahmad S Lateef, Mohammed Y Kamil
    Iraqi Journal for Computer Science and Mathematics, 2023
    Traditional attendance recording methods can be replaced with artificial intelligence (AI) methods. This paper aims to develop an automated attendance system with a user-friendly graphical interface in Arabic to enhance user interaction. The Python programming language is used to build the system, which employs object detection and feature extraction algorithms. This system processes a live broadcast from an IP camera installed in the classroom. The system employs object detection algorithms to detect the faces in the video. The face locations are then sent to the feature extraction algorithms to extract and compare features with the features stored in the database. Our paper concludes that automating the attendance registration process using facial recognition technology can achieve up to 100% accuracy. Comparing our proposed system with previous studies, we find that it outperforms them in several aspects. Our method handles real-time tests with a larger number of students. It accommodates students positioned at different distances from the camera within the classroom, demonstrating our method's effectiveness in automating the attendance registration process.

RECENT SCHOLAR PUBLICATIONS

  • Classification and Prediction of Human Blood Cells Using Artificial Intelligence and Advanced Image Processing Techniques
    AS Lateef, AJM Al-Zuhairi, MY Kamil
    2025
  • Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition
    AS Lateef, MY Kamil
    An-Najah University Journal for Research-A (Natural Sciences) 39 (2), None-None , 2025
    2025
    Citations: 5
  • Face Recognition-Based Automatic Attendance System in a Smart Classroom
    AS Lateef, MY Kamil
    Iraqi Journal for Electrical and Electronic Engineering 20 (1), 37-47 , 2024
    2024
    Citations: 11
  • Facial Recognition Technology-Based AttendanceManagement System Application in Smart Classroom
    AS Lateef, MY Kamil
    Iraqi Journal for Computer Science and Mathematics 4 (3), 12 , 2023
    2023
    Citations: 19

MOST CITED SCHOLAR PUBLICATIONS

  • Facial Recognition Technology-Based AttendanceManagement System Application in Smart Classroom
    AS Lateef, MY Kamil
    Iraqi Journal for Computer Science and Mathematics 4 (3), 12 , 2023
    2023
    Citations: 19
  • Face Recognition-Based Automatic Attendance System in a Smart Classroom
    AS Lateef, MY Kamil
    Iraqi Journal for Electrical and Electronic Engineering 20 (1), 37-47 , 2024
    2024
    Citations: 11
  • Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition
    AS Lateef, MY Kamil
    An-Najah University Journal for Research-A (Natural Sciences) 39 (2), None-None , 2025
    2025
    Citations: 5
  • Classification and Prediction of Human Blood Cells Using Artificial Intelligence and Advanced Image Processing Techniques
    AS Lateef, AJM Al-Zuhairi, MY Kamil
    2025