手写体数字识别系统通过OCON神经网络通过剪枝选择性更新

Q4 Computer Science

模式识别与人工智能 Pub Date : 1992-08-30 DOI:10.1109/ICPR.1992.201862

Shuh-Chuan Tsay, Peir-Ren Hong, Bin-Chang Chieu

{"title":"手写体数字识别系统通过OCON神经网络通过剪枝选择性更新","authors":"Shuh-Chuan Tsay, Peir-Ren Hong, Bin-Chang Chieu","doi":"10.1109/ICPR.1992.201862","DOIUrl":null,"url":null,"abstract":"Performs the handwritten digits recognition using the OCON (one-class-one-net) network and the PSU (pruning selective update) training algorithm. The main feature of the architecture of OCON network is that the entire network is composed of single output multi-layer perceptron and each of the subnets represents one class. The PSU training algorithm defined on the new cost function is designed to speed up the training procedure. It is shown that an OCON network with the new training algorithm outperforms the conventional back-propagation algorithm.<<ETX>>","PeriodicalId":34917,"journal":{"name":"模式识别与人工智能","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1992-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Handwritten digits recognition system via OCON neural network by pruning selective update\",\"authors\":\"Shuh-Chuan Tsay, Peir-Ren Hong, Bin-Chang Chieu\",\"doi\":\"10.1109/ICPR.1992.201862\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Performs the handwritten digits recognition using the OCON (one-class-one-net) network and the PSU (pruning selective update) training algorithm. The main feature of the architecture of OCON network is that the entire network is composed of single output multi-layer perceptron and each of the subnets represents one class. The PSU training algorithm defined on the new cost function is designed to speed up the training procedure. It is shown that an OCON network with the new training algorithm outperforms the conventional back-propagation algorithm.<<ETX>>\",\"PeriodicalId\":34917,\"journal\":{\"name\":\"模式识别与人工智能\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"模式识别与人工智能\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.1992.201862\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"模式识别与人工智能","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/ICPR.1992.201862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}

引用次数: 6

摘要

使用OCON (one-class-one-net)网络和PSU (pruning selective update)训练算法进行手写数字识别。OCON网络结构的主要特点是整个网络由单输出多层感知机组成，每个子网代表一个类。设计了基于新代价函数的PSU训练算法，提高了训练速度。结果表明，采用新训练算法的OCON网络优于传统的反向传播算法。

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

Handwritten digits recognition system via OCON neural network by pruning selective update

Performs the handwritten digits recognition using the OCON (one-class-one-net) network and the PSU (pruning selective update) training algorithm. The main feature of the architecture of OCON network is that the entire network is composed of single output multi-layer perceptron and each of the subnets represents one class. The PSU training algorithm defined on the new cost function is designed to speed up the training procedure. It is shown that an OCON network with the new training algorithm outperforms the conventional back-propagation algorithm.<>

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

模式识别与人工智能 Computer Science-Artificial Intelligence

CiteScore

1.60

自引率

0.00%

发文量

3316

期刊介绍：