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交易数据库中带有空间性约束的关联规则采掘 被引量:2
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作者 刘玉葆 孟志青 《计算机工程与应用》 CSCD 北大核心 2000年第9期110-111,共2页
文章分析了交易数据库中关联规则的不足,提出了一种带有空间性约束的关联规则模型,分析了模型的性质并且通过扩展
关键词 关联规则 数据采掘 交易数据库 空间性约束
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Intraretinal layer segmentation and parameter measurement in optic nerve head region through energy function of spatial-gradient continuity constraint
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作者 CHEN Zai-liang WEI Hao +4 位作者 SHEN Hai-lan PENG Peng YUE Ke-juan LI Jian-feng ZOU Bei-ji 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第8期1938-1947,共10页
For the diagnosis of glaucoma,optical coherence tomography(OCT)is a noninvasive imaging technique for the assessment of retinal layers.To accurately segment intraretinal layers in an optic nerve head(ONH)region,we pro... For the diagnosis of glaucoma,optical coherence tomography(OCT)is a noninvasive imaging technique for the assessment of retinal layers.To accurately segment intraretinal layers in an optic nerve head(ONH)region,we proposed an automatic method for the segmentation of three intraretinal layers in eye OCT scans centered on ONH.The internal limiting membrane,inner segment and outer segment,Bruch’s membrane surfaces under vascular shadows,and interaction of multiple high-reflectivity regions in the OCT image can be accurately segmented through this method.Then,we constructed a novel spatial-gradient continuity constraint,termed spatial-gradient continuity constraint,for the correction of discontinuity between adjacent image segmentation results.In our experiment,we randomly selected 20 B-scans,each annotated three retinal layers by experts.Signed distance errors of?0.80μm obtained through this method are lower than those obtained through the state-of-art method(?1.43μm).Meanwhile,the segmentation results can be used as bases for the diagnosis of glaucoma. 展开更多
关键词 surface segmentation parameter measurement optical coherence tomography optic nerve head spatial-gradient continuity constraints
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A TRUST REGION ALGORITHM WITH NULL SPACE TECHNIQUE FOR EQUALITY CONSTRAINED OPTIMIZATION 被引量:2
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作者 TONGXiaojiao LIDonghui 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2004年第1期54-63,共10页
This paper presents a trust region algorithm with null space technique fornonlinear equality constrained optimization. Considering in the null space methods that,the convergent rate of range space step is faster than ... This paper presents a trust region algorithm with null space technique fornonlinear equality constrained optimization. Considering in the null space methods that,the convergent rate of range space step is faster than the null space step for the most cases,the proposed algorithm computes null steps more often than range space step. Moreover,the new algorithm is based on the reduced Hessian SQP method. Global convergence ofthe proposed algorithm is proved. The effectiveness of the method is demonstrated bysome numerical examples. 展开更多
关键词 trust region method null space technique equality constrained optimization global convergence
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