April D. Logronio, Rona Christine Reyes, N. Linsangan
{"title":"Age Range Classification Through Facial Recognition Using Keras Model","authors":"April D. Logronio, Rona Christine Reyes, N. Linsangan","doi":"10.1109/ICCAE56788.2023.10111149","DOIUrl":null,"url":null,"abstract":"This study focuses on the development of an age range classification through facial recognition and Keras Model using a Raspberry Pi Camera. Keras Model and a convolutional neural network will be implemented to help the age range classification. Raspberry Pi 4 will be incorporated as the microprocessor that the device will use and process the deep learning through this study. The Raspberry Pi Camera v2 is used as the camera sensor that will take faces as input to classify the age range of a subject. Both the Raspberry Pi 4 and camera module will be used to detect a person’s face in real-time and predict the age range of the subject to which the researchers were able to build an age range classification through facial recognition using the Keras Model. The researchers were able to acquire an accuracy of 84.38% upon using Keras Model and convolutional neural network.","PeriodicalId":406112,"journal":{"name":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 15th International Conference on Computer and Automation Engineering (ICCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAE56788.2023.10111149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study focuses on the development of an age range classification through facial recognition and Keras Model using a Raspberry Pi Camera. Keras Model and a convolutional neural network will be implemented to help the age range classification. Raspberry Pi 4 will be incorporated as the microprocessor that the device will use and process the deep learning through this study. The Raspberry Pi Camera v2 is used as the camera sensor that will take faces as input to classify the age range of a subject. Both the Raspberry Pi 4 and camera module will be used to detect a person’s face in real-time and predict the age range of the subject to which the researchers were able to build an age range classification through facial recognition using the Keras Model. The researchers were able to acquire an accuracy of 84.38% upon using Keras Model and convolutional neural network.
本研究的重点是通过使用树莓派相机的面部识别和Keras模型开发年龄范围分类。利用Keras模型和卷积神经网络对年龄范围进行分类。树莓派4将被纳入该设备将使用的微处理器,并通过本研究处理深度学习。Raspberry Pi Camera v2被用作相机传感器,它将人脸作为输入来对受试者的年龄范围进行分类。树莓派4和相机模块都将用于实时检测人脸,并预测受试者的年龄范围,研究人员能够通过使用Keras模型的面部识别建立年龄范围分类。研究人员利用Keras模型和卷积神经网络,获得了84.38%的准确率。