Research on Face Recognition Technology Based on Multi-feature Integration and Deep Learning

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John Smith

Abstract

The development of artificial intelligence and the growing demands of national security and public needs have significantly heightened the focus on face recognition technology, marking it as a critical area of interest within the fields of pattern recognition and computer vision. This technology faces numerous challenges due to variations in facial expressions, poses, lighting conditions, and aging, which often hinder its effective implementation. Current methodologies frequently fall short of meeting the stringent requirements necessary for robust and accurate recognition.To address these challenges, this paper proposes an integrated approach that combines multi-feature face recognition with deep learning techniques. The goal is to enhance the robustness and accuracy of facial feature extraction and classification, thereby supporting the ongoing enhancement and broader application of face recognition technology. This approach aims to provide a foundational framework for future research and practical applications in the field.

Article Details

How to Cite
Smith, J. (2022). Research on Face Recognition Technology Based on Multi-feature Integration and Deep Learning. Journal of Computer Science and Software Applications, 2(2), 35–38. Retrieved from https://mfacademia.org/index.php/jcssa/article/view/115
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