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Research on Face Recognition Method by Autoassociative Memory Based on RNNs

机译:基于RNN的自联想记忆人脸识别方法研究。

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In order to avoid the risk of the biological database being attacked and tampered by hackers, an Autoassociative Memory (AAM) model is proposed in this paper. The model is based on the recurrent neural networks (RNNs) for face recognition, under the condition that the face database is replaced by its model parameters. The stability of the model is proved and analyzed to slack the constraints of AAM model parameters. Besides, a design procedure about solving AAM model parameters is given, and the face recognition method by AAM model is established, which includes image preprocessing, AAM model training, and image recognition. Finally, simulation results on two experiments show the feasibility and performance of the proposed face recognition method.
机译:为了避免生物数据库被黑客攻击和篡改的风险,本文提出了一种自动联想记忆(AAM)模型。该模型基于用于脸部识别的递归神经网络(RNN),条件是将脸部数据库替换为其模型参数。证明并分析了模型的稳定性,以减轻AAM模型参数的约束。给出了求解AAM模型参数的设计过程,建立了基于AAM模型的人脸识别方法,包括图像预处理,AAM模型训练和图像识别。最后,通过两个实验的仿真结果表明了所提出的人脸识别方法的可行性和性能。

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