{"title":"神经网络训练方法在英文和泰文字符识别中的比较","authors":"A. Saenthon, Natchanon Sukkhadamrongrak","doi":"10.1109/APSIPA.2014.7041795","DOIUrl":null,"url":null,"abstract":"Currently, the optical character recognition (OCR) is applied in many fields such as reading the office letter and to read the serial on parts of industrial. The most manufacturing focus the processing time and accuracy for inspection process. The learning method of the optical character recognition is used a neural network to recognize the fonts and correlation the matching value. The neural network has many learning techniques which each technique impact to the processing time and accuracy. Therefore, this paper studies to comparisons a suitable procedure of training in neural network for recognizing both Thai and English characters. The experiment results show the comparing values of error and processing time of each training technique.","PeriodicalId":231382,"journal":{"name":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","volume":"304 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comparison the training methods of neural network for English and Thai character recognition\",\"authors\":\"A. Saenthon, Natchanon Sukkhadamrongrak\",\"doi\":\"10.1109/APSIPA.2014.7041795\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, the optical character recognition (OCR) is applied in many fields such as reading the office letter and to read the serial on parts of industrial. The most manufacturing focus the processing time and accuracy for inspection process. The learning method of the optical character recognition is used a neural network to recognize the fonts and correlation the matching value. The neural network has many learning techniques which each technique impact to the processing time and accuracy. Therefore, this paper studies to comparisons a suitable procedure of training in neural network for recognizing both Thai and English characters. The experiment results show the comparing values of error and processing time of each training technique.\",\"PeriodicalId\":231382,\"journal\":{\"name\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"volume\":\"304 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPA.2014.7041795\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2014.7041795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison the training methods of neural network for English and Thai character recognition
Currently, the optical character recognition (OCR) is applied in many fields such as reading the office letter and to read the serial on parts of industrial. The most manufacturing focus the processing time and accuracy for inspection process. The learning method of the optical character recognition is used a neural network to recognize the fonts and correlation the matching value. The neural network has many learning techniques which each technique impact to the processing time and accuracy. Therefore, this paper studies to comparisons a suitable procedure of training in neural network for recognizing both Thai and English characters. The experiment results show the comparing values of error and processing time of each training technique.