{"title":"基于人工智能的手写阿拉伯文字离线识别系统","authors":"Feisal Alaswad, P. E, Hazem Issa","doi":"10.1109/SPIN52536.2021.9565957","DOIUrl":null,"url":null,"abstract":"Arabic alphabets are used in more than 25 languages such as Arabic, Persian, Kurdish, Urdu etc. In this research work it is planned to build a computer system for recognizing handwritten Arabic words. We used sequence vector technique to recognize the Arabic words. Multi-layer Networks structure and Back-propagation Training are used as tools to decide. Also, for special cases of handling identicalness vectors, special feature extraction technique is applied. Experiments were performed by writing code in MATLAB, which achieved average accuracy of more than 92%.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Off-Line Recognition System for Handwritten Arabic Words Using Artificial Intelligence\",\"authors\":\"Feisal Alaswad, P. E, Hazem Issa\",\"doi\":\"10.1109/SPIN52536.2021.9565957\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Arabic alphabets are used in more than 25 languages such as Arabic, Persian, Kurdish, Urdu etc. In this research work it is planned to build a computer system for recognizing handwritten Arabic words. We used sequence vector technique to recognize the Arabic words. Multi-layer Networks structure and Back-propagation Training are used as tools to decide. Also, for special cases of handling identicalness vectors, special feature extraction technique is applied. Experiments were performed by writing code in MATLAB, which achieved average accuracy of more than 92%.\",\"PeriodicalId\":343177,\"journal\":{\"name\":\"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPIN52536.2021.9565957\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIN52536.2021.9565957","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Off-Line Recognition System for Handwritten Arabic Words Using Artificial Intelligence
Arabic alphabets are used in more than 25 languages such as Arabic, Persian, Kurdish, Urdu etc. In this research work it is planned to build a computer system for recognizing handwritten Arabic words. We used sequence vector technique to recognize the Arabic words. Multi-layer Networks structure and Back-propagation Training are used as tools to decide. Also, for special cases of handling identicalness vectors, special feature extraction technique is applied. Experiments were performed by writing code in MATLAB, which achieved average accuracy of more than 92%.
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