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All Journal Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Ayaz Khalid Mohammed
Computer System Department, Ararat Technical Private Institute, Kurdistan Region – Iraq
Computer Science & IT 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.
Co-Authors Anik Vega Vitianingsih Firas Mahmood Mustafa Hewa Zangana Marwan Omar