{"title":"使用 \"只看一次 \"算法检测 Sunda 脚本","authors":"Daffa Arifadilah, Asriyanik, Agung Pambudi","doi":"10.59934/jaiea.v3i2.443","DOIUrl":null,"url":null,"abstract":"The Sundanese script is a writing system used in the Sundanese language, one of the regional languages of West Java, Indonesia. This study investigates the use of the YOLO v8 algorithm for the real-time video detection of Sundanese script. Various versions of YOLO v8, including YOLO v8n, v8s, v8m, v8l, and v8x, were tested to determine the most effective model. After a comprehensive evaluation involving the analysis of mean Average Precision (mAP), F1-Confidence, and precision, the study selected the YOLO v8s model as the primary detection method. YOLO v8s demonstrated superior performance with the highest mAP of 98.835%, an F1-Confidence of 98%, and a precision of 76,2%. This choice was based on a balance between high accuracy and computational efficiency. The results indicate significant potential for object recognition technology in the learning and preservation of Sundanese script.","PeriodicalId":320979,"journal":{"name":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","volume":"110 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sunda Script Detection Using You Only Look Once Algorithm\",\"authors\":\"Daffa Arifadilah, Asriyanik, Agung Pambudi\",\"doi\":\"10.59934/jaiea.v3i2.443\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Sundanese script is a writing system used in the Sundanese language, one of the regional languages of West Java, Indonesia. This study investigates the use of the YOLO v8 algorithm for the real-time video detection of Sundanese script. Various versions of YOLO v8, including YOLO v8n, v8s, v8m, v8l, and v8x, were tested to determine the most effective model. After a comprehensive evaluation involving the analysis of mean Average Precision (mAP), F1-Confidence, and precision, the study selected the YOLO v8s model as the primary detection method. YOLO v8s demonstrated superior performance with the highest mAP of 98.835%, an F1-Confidence of 98%, and a precision of 76,2%. This choice was based on a balance between high accuracy and computational efficiency. The results indicate significant potential for object recognition technology in the learning and preservation of Sundanese script.\",\"PeriodicalId\":320979,\"journal\":{\"name\":\"Journal of Artificial Intelligence and Engineering Applications (JAIEA)\",\"volume\":\"110 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Artificial Intelligence and Engineering Applications (JAIEA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.59934/jaiea.v3i2.443\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence and Engineering Applications (JAIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59934/jaiea.v3i2.443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sunda Script Detection Using You Only Look Once Algorithm
The Sundanese script is a writing system used in the Sundanese language, one of the regional languages of West Java, Indonesia. This study investigates the use of the YOLO v8 algorithm for the real-time video detection of Sundanese script. Various versions of YOLO v8, including YOLO v8n, v8s, v8m, v8l, and v8x, were tested to determine the most effective model. After a comprehensive evaluation involving the analysis of mean Average Precision (mAP), F1-Confidence, and precision, the study selected the YOLO v8s model as the primary detection method. YOLO v8s demonstrated superior performance with the highest mAP of 98.835%, an F1-Confidence of 98%, and a precision of 76,2%. This choice was based on a balance between high accuracy and computational efficiency. The results indicate significant potential for object recognition technology in the learning and preservation of Sundanese script.