Thanapong Khajontantichaikun, S. Jaiyen, S. Yamsaengsung, P. Mongkolnam, Thanitsorn Chirapornchai
{"title":"基于YOLOv7的泰国老年人面部情绪检测","authors":"Thanapong Khajontantichaikun, S. Jaiyen, S. Yamsaengsung, P. Mongkolnam, Thanitsorn Chirapornchai","doi":"10.1109/KST57286.2023.10086786","DOIUrl":null,"url":null,"abstract":"Currently, many countries around the world are moving towards becoming an aging society. The mental health of the elderly is one of the key challenges in an aging society. In this research, the use of YOLOv7 for facial emotion detection in Thai elderly is examined. In the experiments, the performance of YOLOv7 is compared to Faster R-CNN and SSD. All models are trained and tested with a facial dataset of Thai elderly people. From the experimental result, YOLOv7 achieved the best performance among the compared models with the mean average precision of 0.95 while Faster R-CNN and SSD have the mean average precision of 0.86 and 0.84, respectively.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Facial Emotion Detection for Thai Elderly People using YOLOv7\",\"authors\":\"Thanapong Khajontantichaikun, S. Jaiyen, S. Yamsaengsung, P. Mongkolnam, Thanitsorn Chirapornchai\",\"doi\":\"10.1109/KST57286.2023.10086786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, many countries around the world are moving towards becoming an aging society. The mental health of the elderly is one of the key challenges in an aging society. In this research, the use of YOLOv7 for facial emotion detection in Thai elderly is examined. In the experiments, the performance of YOLOv7 is compared to Faster R-CNN and SSD. All models are trained and tested with a facial dataset of Thai elderly people. From the experimental result, YOLOv7 achieved the best performance among the compared models with the mean average precision of 0.95 while Faster R-CNN and SSD have the mean average precision of 0.86 and 0.84, respectively.\",\"PeriodicalId\":351833,\"journal\":{\"name\":\"2023 15th International Conference on Knowledge and Smart Technology (KST)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 15th International Conference on Knowledge and Smart Technology (KST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KST57286.2023.10086786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 15th International Conference on Knowledge and Smart Technology (KST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KST57286.2023.10086786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Facial Emotion Detection for Thai Elderly People using YOLOv7
Currently, many countries around the world are moving towards becoming an aging society. The mental health of the elderly is one of the key challenges in an aging society. In this research, the use of YOLOv7 for facial emotion detection in Thai elderly is examined. In the experiments, the performance of YOLOv7 is compared to Faster R-CNN and SSD. All models are trained and tested with a facial dataset of Thai elderly people. From the experimental result, YOLOv7 achieved the best performance among the compared models with the mean average precision of 0.95 while Faster R-CNN and SSD have the mean average precision of 0.86 and 0.84, respectively.
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