Advanced convolutional neural network frameworks for robust multi-angle facial authentication: implementation and comparative evaluation
Abstract
Advanced convolutional neural network frameworks for robust multi-angle facial authentication: implementation and comparative evaluation
Incoming article date: 08.04.2025This article presents the technical implementation of a convolutional nueral network-based face recognition system that is able to work under variable scenarios like occlusion, angle changes, and camera rotation. various face identification algorithms were analysed with the purpose of developing a model that could identify faces at different angles. The system was experimentally verified with various datasets and compared to its accuracy, processing speed, and robustness towards environmental disturbance. Results indicate that our convolutioan neural network structure optimized achieves 90%+ accuracy under pristine conditions and maintains decent performance upon partial occlusion.
Keywords: face detection, convolutional nueral networks, model, feature extraction, deep learning, face recognition, image