Muhammad Helmy Faishal, M. D. Sulistiyo, Aditya Firman Ihsan
{"title":"使用更快的 R-CNN 检测爪哇语字母","authors":"Muhammad Helmy Faishal, M. D. Sulistiyo, Aditya Firman Ihsan","doi":"10.24014/ijaidm.v6i2.24641","DOIUrl":null,"url":null,"abstract":"The Javanese script is now rarely used, and some people no longer recognize it. The construction of a Javanese script recognition system based on digital image processing is one of its preservation efforts. This study proposes a model capable of detecting and recognizing Javanese characters using Faster R-CNN to help people who are not familiar with the Javanese script. Faster R-CNN was chosen because it does not require additional processing compared to the previous method and Faster R-CNN has better accuracy and the ability to detect small objects. Faster R-CNN shows good results in text detection, but the use of Faster R-CNN in detecting Javanese script has not been found which makes its performance unknown, so this study will show how Faster R-CNN performs in detecting Javanese script. In this study, Faster R-CNN was able to show good performance by obtaining mean average precision (mAP) values up to 0.8381, accuracy up to 96.31%, precision up to 96.53%, recall up to 96.38 %, and F1-Score up to 96.41%. These results indicate that Faster R-CNN has better results than the previous method and can detect Javanese characters well.","PeriodicalId":385582,"journal":{"name":"Indonesian Journal of Artificial Intelligence and Data Mining","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Javanese Script Letter Detection Using Faster R-CNN\",\"authors\":\"Muhammad Helmy Faishal, M. D. Sulistiyo, Aditya Firman Ihsan\",\"doi\":\"10.24014/ijaidm.v6i2.24641\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Javanese script is now rarely used, and some people no longer recognize it. The construction of a Javanese script recognition system based on digital image processing is one of its preservation efforts. This study proposes a model capable of detecting and recognizing Javanese characters using Faster R-CNN to help people who are not familiar with the Javanese script. Faster R-CNN was chosen because it does not require additional processing compared to the previous method and Faster R-CNN has better accuracy and the ability to detect small objects. Faster R-CNN shows good results in text detection, but the use of Faster R-CNN in detecting Javanese script has not been found which makes its performance unknown, so this study will show how Faster R-CNN performs in detecting Javanese script. In this study, Faster R-CNN was able to show good performance by obtaining mean average precision (mAP) values up to 0.8381, accuracy up to 96.31%, precision up to 96.53%, recall up to 96.38 %, and F1-Score up to 96.41%. These results indicate that Faster R-CNN has better results than the previous method and can detect Javanese characters well.\",\"PeriodicalId\":385582,\"journal\":{\"name\":\"Indonesian Journal of Artificial Intelligence and Data Mining\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Indonesian Journal of Artificial Intelligence and Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24014/ijaidm.v6i2.24641\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indonesian Journal of Artificial Intelligence and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24014/ijaidm.v6i2.24641","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Javanese Script Letter Detection Using Faster R-CNN
The Javanese script is now rarely used, and some people no longer recognize it. The construction of a Javanese script recognition system based on digital image processing is one of its preservation efforts. This study proposes a model capable of detecting and recognizing Javanese characters using Faster R-CNN to help people who are not familiar with the Javanese script. Faster R-CNN was chosen because it does not require additional processing compared to the previous method and Faster R-CNN has better accuracy and the ability to detect small objects. Faster R-CNN shows good results in text detection, but the use of Faster R-CNN in detecting Javanese script has not been found which makes its performance unknown, so this study will show how Faster R-CNN performs in detecting Javanese script. In this study, Faster R-CNN was able to show good performance by obtaining mean average precision (mAP) values up to 0.8381, accuracy up to 96.31%, precision up to 96.53%, recall up to 96.38 %, and F1-Score up to 96.41%. These results indicate that Faster R-CNN has better results than the previous method and can detect Javanese characters well.