Deep Face Recognition for Imperfect Human Face Images on Social Media using the CNN Method

Shifa Inges Yudita, T. Mantoro, M. A. Ayu
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引用次数: 2

Abstract

Face recognition systems nowadays are applied in any gadget. The usual purpose of this technology is to recognize people's information for security purposes on a smartphone. Unfortunately, this face recognition is only available for perfect facial data. In some cases, there are situations where full faces may not be available on social media and recognizing imperfect human facial structure is not a simple task. The aim of this study is to provide the capability to recognize human faces based on partial or imperfect human facial data. This study explores the idea of face recognition based on partial or imperfect human facial data using the state art convolutional neural network-based architecture, especially for the CNN model with the pre-trained VGG-Face model which promises a good recognizing imperfect image of human face results.
使用CNN方法对社交媒体上不完美人脸图像进行深度人脸识别
如今,人脸识别系统应用于任何小工具。这项技术通常的目的是为了安全目的在智能手机上识别人们的信息。不幸的是,这种面部识别只适用于完美的面部数据。在某些情况下,社交媒体上可能看不到完整的脸,识别不完美的人脸结构并不是一件简单的任务。本研究的目的是提供基于部分或不完整人脸数据的人脸识别能力。本研究利用最先进的基于卷积神经网络的架构,探索了基于部分或不完美人脸数据的人脸识别思想,特别是采用预训练的VGG-Face模型的CNN模型,可以很好地识别不完美的人脸图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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