基于卷积神经网络(CNN)图像的悲伤情绪和抑郁分类

Muhammad Fathur Prayuda
{"title":"基于卷积神经网络(CNN)图像的悲伤情绪和抑郁分类","authors":"Muhammad Fathur Prayuda","doi":"10.32493/informatika.v6i1.8433","DOIUrl":null,"url":null,"abstract":"The human face has various functions, especially in expressing something. The expression shown has a unique shape so that it can recognize the atmosphere of the feeling that is being felt. The appearance of a feeling is usually caused by emotion. Research on the classification of emotions has been carried out using various methods. For this study, a Convolutional Neural Network (CNN) method was used which serves as a classifier for sad and depressive emotions. The CNN method has the advantage of preprocessing convolution so that it can extract a hidden feature in an image. The dataset used in this study came from the Facial expression dataset image folders (fer2013) where the dataset used for classification was taken with a ratio of 60% training and 40% validation with the results of the trained model of 60% total loss and 68% test accuracy.","PeriodicalId":251854,"journal":{"name":"Jurnal Informatika Universitas Pamulang","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of Sad Emotions and Depression Through Images Using Convolutional Neural Network (CNN)\",\"authors\":\"Muhammad Fathur Prayuda\",\"doi\":\"10.32493/informatika.v6i1.8433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The human face has various functions, especially in expressing something. The expression shown has a unique shape so that it can recognize the atmosphere of the feeling that is being felt. The appearance of a feeling is usually caused by emotion. Research on the classification of emotions has been carried out using various methods. For this study, a Convolutional Neural Network (CNN) method was used which serves as a classifier for sad and depressive emotions. The CNN method has the advantage of preprocessing convolution so that it can extract a hidden feature in an image. The dataset used in this study came from the Facial expression dataset image folders (fer2013) where the dataset used for classification was taken with a ratio of 60% training and 40% validation with the results of the trained model of 60% total loss and 68% test accuracy.\",\"PeriodicalId\":251854,\"journal\":{\"name\":\"Jurnal Informatika Universitas Pamulang\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Informatika Universitas Pamulang\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32493/informatika.v6i1.8433\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Informatika Universitas Pamulang","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32493/informatika.v6i1.8433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

人脸有多种功能,尤其是在表达某些东西时。所显示的表情具有独特的形状,因此它可以识别所感受到的感觉的氛围。一种感觉的出现通常是由情绪引起的。关于情绪分类的研究已经用各种方法进行了。在本研究中,使用卷积神经网络(CNN)方法作为悲伤和抑郁情绪的分类器。CNN方法具有预处理卷积的优点,可以提取图像中的隐藏特征。本研究使用的数据集来自面部表情数据集图像文件夹(fer2013),其中用于分类的数据集以60%的训练和40%的验证比例进行,训练后的模型总损失为60%,测试准确率为68%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Sad Emotions and Depression Through Images Using Convolutional Neural Network (CNN)
The human face has various functions, especially in expressing something. The expression shown has a unique shape so that it can recognize the atmosphere of the feeling that is being felt. The appearance of a feeling is usually caused by emotion. Research on the classification of emotions has been carried out using various methods. For this study, a Convolutional Neural Network (CNN) method was used which serves as a classifier for sad and depressive emotions. The CNN method has the advantage of preprocessing convolution so that it can extract a hidden feature in an image. The dataset used in this study came from the Facial expression dataset image folders (fer2013) where the dataset used for classification was taken with a ratio of 60% training and 40% validation with the results of the trained model of 60% total loss and 68% test accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信