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FAREC — CNN based efficient face recognition technique using Dlib

机译:Farec-CNN基于CNN高效的人脸识别技术使用DLIB

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Despite of advancement in face recognition, it has received much more attention in last few decades in the field of research and in commercial markets this project proposes an efficient technique for face recognition system based on Deep Learning using Convolutional Neural Network (CNN) with Dlib face alignment. The paper describes the process involved in the face recognition like face alignment and feature extraction. The paper also emphasizes the importance of the face alignment, thus the accuracy and False Acceptance Rate (FAR) is observed by using proposed technique. The computational analysis shows the better performance than other state-of-art approaches. The work has been done on Face Recognition Grand challenge (FRGC) dataset and giving accuracy of 96% with FAR of 0.1.
机译:尽管对人们的进步发展,但在过去几十年中,它在研究领域和商业市场中获得了更高的关注该项目,该项目提出了一种基于深入学习的基于Dlib面部的深度学习的人脸识别系统技术结盟。本文介绍了面部对准和特征提取等面部识别所涉及的过程。本文还强调了面部对准的重要性,因此通过使用所提出的技术观察到精度和假接受率(远)。计算分析显示比其他最先进的方法更好的性能。这项工作已经完成了面部识别大挑战(FRGC)数据集,并提供96%的准确性,远远为0.1。

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