Thaer Thaher1,*, Muhammed Saffarini2, Majdi Mafarja3, Abdulaziz Alashbi4, Abdul Hakim Mohamed5, Ayman A. El-Saleh6
CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2359-2394, 2025, DOI:10.32604/cmes.2025.065388
- 31 August 2025
Abstract Face detection is a critical component in modern security, surveillance, and human-computer interaction systems, with widespread applications in smartphones, biometric access control, and public monitoring. However, detecting faces with high levels of occlusion, such as those covered by masks, veils, or scarves, remains a significant challenge, as traditional models often fail to generalize under such conditions. This paper presents a hybrid approach that combines traditional handcrafted feature extraction technique called Histogram of Oriented Gradients (HOG) and Canny edge detection with modern deep learning models. The goal is to improve face detection accuracy under occlusions. The… More >
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