Design and Development of Efficient Face Recognition Architecture using Neural Network on FPGA

被引：0

作者：

Ahmed, M. Tousif ^{[1
]}

Sinha, Sanjay ^{[1
]}

机构：

[1] Xvidia Technol, Bengaluru, India

来源：

PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS) | 2018年

关键词：

FPGA; Face Recognition System(FRS); Neural Networks (NN); Histogram of Oriented Gradients (HOG);

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Face Recognition is an application used for identification of a person among the pool of images. The main goal is to identify the face among the database of images. As the geometrical features of the face images are similar, distinguishing one face from other faces from the other base is challenging task. The Proposed work uses the Neural Network as classifier using Histogram of Oriented Gradients features of images. The proposed architecture uses Levenberg-Marquardt feed-forward training method for neural network. ORL data base is used and is implemented on VIRTEX-7 FPGA platform giving better recognition rate and high performance.

引用

页码：905 / 909

页数：5

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