畸变不变手写体数字识别的自适应共振理论(ART)神经网络模型

[Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society Pub Date : 1990-11-27 DOI:10.1109/IECON.1990.149319

E. Khan

{"title":"畸变不变手写体数字识别的自适应共振理论(ART)神经网络模型","authors":"E. Khan","doi":"10.1109/IECON.1990.149319","DOIUrl":null,"url":null,"abstract":"A distortion- and rotation-invariant handwritten digit recognition scheme using a modified version of the adaptive resonance theory neural network model proposed by S. Grossberg and G. Carpenter (1988) is reported. The scheme is robust. It can be extended to the recognition of other handwritten characters.<<ETX>>","PeriodicalId":253424,"journal":{"name":"[Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Distortion invariant handwritten digit recognition using adaptive resonance theory (ART) neural net model\",\"authors\":\"E. Khan\",\"doi\":\"10.1109/IECON.1990.149319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A distortion- and rotation-invariant handwritten digit recognition scheme using a modified version of the adaptive resonance theory neural network model proposed by S. Grossberg and G. Carpenter (1988) is reported. The scheme is robust. It can be extended to the recognition of other handwritten characters.<<ETX>>\",\"PeriodicalId\":253424,\"journal\":{\"name\":\"[Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IECON.1990.149319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IECON.1990.149319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

本文报道了一种使用S. Grossberg和G. Carpenter(1988)提出的自适应共振理论神经网络模型的改进版本的失真和旋转不变手写数字识别方案。该方案是健壮的。它可以扩展到其他手写字符的识别。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Distortion invariant handwritten digit recognition using adaptive resonance theory (ART) neural net model

A distortion- and rotation-invariant handwritten digit recognition scheme using a modified version of the adaptive resonance theory neural network model proposed by S. Grossberg and G. Carpenter (1988) is reported. The scheme is robust. It can be extended to the recognition of other handwritten characters.<>

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

[Proceedings] IECON '90: 16th Annual Conference of IEEE Industrial Electronics Society

CiteScore

1.40

自引率

0.00%

发文量