{"title":"比较性能指标的模糊ARTMAP,学习矢量量化,和反向传播手写字符识别","authors":"G. Carpenter, S. Grossberg, K. Iizuka","doi":"10.1109/IJCNN.1992.287090","DOIUrl":null,"url":null,"abstract":"The authors compare the performance of fuzzy ARTMAP with that of learned vector quantization and backpropagation on a handwritten character recognition task. Training with fuzzy ARTMAP to a fixed criterion used many fewer epochs. Voting with fuzzy ARTMAP yielded the highest recognition rates.<<ETX>>","PeriodicalId":286849,"journal":{"name":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"50","resultStr":"{\"title\":\"Comparative performance measures of fuzzy ARTMAP, learned vector quantization, and back propagation for handwritten character recognition\",\"authors\":\"G. Carpenter, S. Grossberg, K. Iizuka\",\"doi\":\"10.1109/IJCNN.1992.287090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors compare the performance of fuzzy ARTMAP with that of learned vector quantization and backpropagation on a handwritten character recognition task. Training with fuzzy ARTMAP to a fixed criterion used many fewer epochs. Voting with fuzzy ARTMAP yielded the highest recognition rates.<<ETX>>\",\"PeriodicalId\":286849,\"journal\":{\"name\":\"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"50\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1992.287090\",\"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 1992] IJCNN International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1992.287090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative performance measures of fuzzy ARTMAP, learned vector quantization, and back propagation for handwritten character recognition
The authors compare the performance of fuzzy ARTMAP with that of learned vector quantization and backpropagation on a handwritten character recognition task. Training with fuzzy ARTMAP to a fixed criterion used many fewer epochs. Voting with fuzzy ARTMAP yielded the highest recognition rates.<>