情感识别系统的深度卷积神经网络实现

Rabie Helaly, Mohamed Ali Hajjaji, F. M'sahli, A. Mtibaa
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引用次数: 4

摘要

本文提出了一种基于深度学习模型的人脸识别系统。所提出的工作在嵌入式系统Raspberry Pi 4上实现。为此,我们选择了“异常卷积神经网络”模型来实现我们的情感系统识别。将注册好的人脸图像输入到嵌入式系统的分类器中,分类器将其分类为7种面部表情。为了进行实验,使用了“Fer 2013”数据集。该模型在图形处理单元(GPU)上的准确率达到94%。在嵌入式系统上实现后,根据他对GPU性能的限制,在Raspberry Pi 4上的准确率为89%。与其他近期作品相比
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Convolution Neural Network Implementation for Emotion Recognition System
In this paper, we present a facial recognition system based on deep learning model. The proposed work is implemented on the embedded system named Raspberry Pi 4. For this, the “Xception convolutional neural network” model is chosen to achieve our emotion system recognition. The registered facial images are taken as input into the classifiers in the embedded system which classifies them into seven facial expressions. For the conduction of the experiment “Fer 2013” data set is used. The proposed model gives an accuracy of 94 % in Graphics Processing Unit” (GPU). After his implementation on the embedded system, according to his limitation against GPU performances, The accuracy is 89% on Raspberry Pi 4. Comparing to other recent works
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