QQ客服 官方微博 反馈留言

	Learning from Error: A two-level combined model for image classification
	Jiang, Mingyang ; Li, Chunxiao ; Deng, Zirui ; Feng, Jufu ; Wang, Liwei
	2011
英文摘要	We propose an error learning model for image classification. Motivated by the observation that classifiers trained using local grid regions of the images are often biased, i.e., contain many classification error, we present a two-level combined model to learn useful classification information from these errors, based on Bayes rule. We give theoretical analysis and explanation to show that this error learning model is effective to correct the classification errors made by the local region classifiers. We conduct extensive experiments on benchmark image classification datasets, promising results are obtained.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000313291600137&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Hardware & Architecture; EI; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1109/ACPR.2011.6166669
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/293130]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Jiang, Mingyang,Li, Chunxiao,Deng, Zirui,et al. Learning from Error: A two-level combined model for image classification. 2011-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。