Published on: April 2026
DEEP LEARNING FOR FACIAL RECOGNITION AND DETECTION
VIBHOR
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Abstract
Face recognition is one of the most active and challenging research areas in computer vision and biometric authentication. This paper presents a comprehensive face recognition system built upon machine learning and deep learning techniques, targeting accurate, real-time identification of human faces under unconstrained environments. The proposed system employs a multi-stage pipeline comprising image acquisition, preprocessing, feature extraction using Convolutional Neural Networks (CNNs), and classification using Support Vector Machines (SVMs) and deep neural architectures.
How to Cite this Paper
VIBHOR, (2026). Deep Learning for Facial Recognition and Detection. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.443
VIBHOR, . "Deep Learning for Facial Recognition and Detection." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.443.
VIBHOR, . "Deep Learning for Facial Recognition and Detection." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.443.
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- •Published on: Apr 16 2026
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