HTM人脸识别的生物记忆模型

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) Pub Date : 2016-11-02 DOI:10.1109/ICACCI.2016.7732265

O. Krestinskaya, A. P. James

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引用次数: 3

摘要

受人类记忆工作原理的启发，我们提出了一种新的算法来存储从图像中检测到的HTM特征。与现有的HTM训练集相比，训练集的结果特征需要更少的内存。使用基准AR数据集在人脸识别问题中测试了所提出的特征。仿真结果表明，与传统的人脸识别方法相比，该算法具有更高的人脸识别精度。

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Bioinspired memory model for HTM face recognition

Inspired from the working principle of human memory, we propose a new algorithm for storing HTM features detected from images. The resulting features from the training set require lower memory than existing HTM training set. The proposed features are tested in a face recognition problem using the benchmark AR dataset. the simulation results show that the proposed algorithm gives higher face recognition accuracy, in comparison to the conventional methods.

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2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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