Chiun-Li Chin, Zih-Yi Yang, Rui-Cih Su, Cheng-Shiun Yang
{"title":"A Facial Pore Aided Detection System Using CNN Deep Learning Algorithm","authors":"Chiun-Li Chin, Zih-Yi Yang, Rui-Cih Su, Cheng-Shiun Yang","doi":"10.1109/ICAWST.2018.8517224","DOIUrl":null,"url":null,"abstract":"Many people are concerned about their facial skin maintenance. Rough pore is one of the facial skin problems which annoyed many people. The size of facial pore is tiny, and it has various shapes. Therefore, it is difficult to recognize facial pore by using traditional image processing. In this paper, we propose an approach based on convolutional neural networks (CNNs) to develop a facial pore aided detection system. We use the LeNet−5 model as our benchmark architecture, and investigate the performance of different depths network on our facial pore dataset. The facial pore aided detection system will help people understand more about their facial skin problems and properly keep their facial skin well.","PeriodicalId":277939,"journal":{"name":"2018 9th International Conference on Awareness Science and Technology (iCAST)","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 9th International Conference on Awareness Science and Technology (iCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAWST.2018.8517224","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Many people are concerned about their facial skin maintenance. Rough pore is one of the facial skin problems which annoyed many people. The size of facial pore is tiny, and it has various shapes. Therefore, it is difficult to recognize facial pore by using traditional image processing. In this paper, we propose an approach based on convolutional neural networks (CNNs) to develop a facial pore aided detection system. We use the LeNet−5 model as our benchmark architecture, and investigate the performance of different depths network on our facial pore dataset. The facial pore aided detection system will help people understand more about their facial skin problems and properly keep their facial skin well.