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All Journal International Journal of Research and Applied Technology (INJURATECH) Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Ayaz Khalid Mohammed
Computer System Department, Ararat Technical Private Institute, Kurdistan Region – Iraq
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering Transportation

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Adaptive Resonance Theory-Based Approach for Robust and Efficient Face Recognition Hewa Zangana; Ayaz Khalid Mohammed; Marwan Omar; Firas Mahmood Mustafa; Anik Vega Vitianingsih
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.38709

Abstract

Face recognition systems play a crucial role in security, surveillance, and authentication applications. However, traditional deep learning-based models, particularly Convolutional Neural Networks (CNNs), often struggle with issues such as varying lighting conditions, occlusions, and high computational costs. This paper proposes an Adaptive Resonance Theory (ART)-based face recognition framework that enhances recognition robustness and computational efficiency. Unlike CNNs, ART enables incremental learning without requiring retraining, making it suitable for realtime applications. The study evaluated the proposed system on threebenchmark datasets: LFW, Yale, and ORL. Experimental results indicate that the ART-based model achieved an average accuracy of 96.2%, outperforming CNN-based models (93.5%) while reducing recognition time by 25%. Additionally, ART demonstrated superior adaptability, maintaining recognition accuracy above 94% even under occlusion and low-light conditions. These findings confirm the effectiveness of ART-based face recognition for security, access control, and innovative surveillance applications. Future research will focus on integrating ART with deep learning techniques for enhanced performance in large-scale datasets.
Cybernetic Deception: Unraveling the Layers of Email Phishing Threats Hewa Majeed Zangana; Ayaz Khalid Mohammed; Amira Bibo Sallow; Zina Bibo Sallow
International Journal of Research and Applied Technology Vol. 4 No. 1 (2024): International Journal of Research and Applied Technology (INJURATECH)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injuratech.v4i1.13620

Abstract

E-mail phishing, a tireless and versatile cybersecurity risk, requires a intensive examination to fortify organizational resistances. This broad survey dives into the multifaceted measurements of e-mail phishing, including mental control strategies, mechanical complexities, and real-world experiences determined from assorted case considers. The investigation of location and anticipation procedures covers a extend of commitments, tending to half breed machine learning approaches, the significance of client instruction, and the part of administrative compliance. These procedures give a significant system for organizations pointing to improve their flexibility against the energetic scene of phishing strategies. The theoretical underscores the administrative landscape's significant part in forming cybersecurity hones, advertising a organized establishment for organizations to adjust with legitimate prerequisites. Expecting future patterns and challenges, such as the integration of characteristic dialect preparing procedures and the complexities of cloud-based phishing assaults, gets to be basic for maintained cyber versatility. In conclusion, this paper serves as a comprehensive direct, enabling people and organizations with the information and methodologies required to explore the complex scene of e-mail phishing dangers. It recognizes the energetic nature of the danger scene, highlighting the progressing travel in combating computerized duplicity and invigorating preparation against the ever-evolving strategies of phishing foes.
Co-Authors Amira Bibo Sallow Anik Vega Vitianingsih Firas Mahmood Mustafa Hewa Majeed Zangana Hewa Zangana Marwan Omar Zina Bibo Sallow