DEVELOPING A DEEP LEARNING-BASED METHODOLOGY FOR FACIAL RECOGNITION IN REAL-TIME SYSTEM
Abstract
This study focuses on developing a cutting-edge deep learning-based methodology for real-time facial recognition, with a particular application to images of Elon Musk. The introduction highlights the significance of facial recognition technology in diverse fields. Aims and objectives center around achieving superior accuracy, speed, and robustness in the identification of Elon Musk's face. The methodology employs advanced deep learning techniques, emphasizing adaptability to diverse scenarios. Major findings reveal the developed system's exceptional accuracy and speed, with robust performance under varied conditions, despite a slight dip in accuracy in low-light environments. Recommendations include refining the system for enhanced performance in low-light scenarios and optimizing computational resources.
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