How computational neuroscience could help improving face recognition systems?

S. Karimimehr, M. Yazdchi
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引用次数: 3

Abstract

Computational neuroscience is a growing discipline in science, which tries to understand the operations of human brain and inspire from it as a new computational paradigm. Face recognition is an important question both in pattern recognition and neuroscience. In the last few years, neuroscientists found many facts about object recognition in primate's brain. Here, we propose a cortex inspired face recognition system which uses some findings about the brain such as the operations of feature extractor cells in visual cortex and the function of attention in discarding distracting parts of the images. Now it is the time to merge the knowledge of learning systems with biological findings. The proposed method named Advanced Neurologically Inspires Face recognition (ANIF) system is compared with previous model NIF and some well-known face recognition algorithms within different datasets, which shows remarkable results.
计算神经科学如何帮助改进人脸识别系统?
计算神经科学是一门新兴的科学学科,它试图理解人类大脑的运作,并从中启发一种新的计算范式。人脸识别是模式识别和神经科学中的一个重要问题。在过去的几年里,神经科学家发现了许多关于灵长类动物大脑中物体识别的事实。在这里,我们提出了一个皮层启发的人脸识别系统,该系统利用了一些关于大脑的发现,如视觉皮层中的特征提取细胞的运作和注意力在丢弃图像中分散部分的功能。现在是时候将学习系统的知识与生物学发现结合起来了。在不同的数据集上,将该方法与已有的神经启发人脸识别算法和一些知名的人脸识别算法进行了比较,取得了显著的效果。
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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