Search - matlab DeBoor

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[Other resource] Bspline DL : 0: 采用MATLAB编写B样条绘制程序，可以选择四种节点矢量，采用Deboor算法,详细参看计算机辅助几何设计的书籍(CAGD)
Update : 2008-10-13 Size : 9.01kb Publisher : yanxing
[matlab] deBoor DL : 0: de Boor 求值算法求作二次和三次B-样条曲线非插值，给定顶点-algorithm evaluates demand for secondary and cubic B-spline- curve interpolation, given vertex
Update : 2025-02-17 Size : 2kb Publisher : jo Wang
[AI-NN-PR] deboor-cox DL : 1: 目的:运用强化学习!多分类器集成!降维方法等最新计算机技术,结合细胞病理知识,设计制作/智能化肺癌细胞病理图像诊断系统0"方法:采集细胞图像,运用基于强化学习的图像分割法将细胞区域从背景中分离出来运用基于样条和改进2方法对重叠细胞进行分离和重构提取40个细胞特征用于贝叶斯!支持向量机!紧邻和决策树4种分类器,集成产生肺癌细胞分类结果建立肺癌细胞病理图库,运用基于等降维方法对细胞进行比对,给予未定型癌细胞分类"结果:/智能化肺癌细胞病理诊断系统0应用于临床随机1200例肺部病灶穿刺细胞学涂片,肺癌识别诊断率94180 ,假阳性率1185 ,假阴性率3135 ,肺癌分类识别率82190 ,核异型细胞识别率74120 "结论:/智能化肺癌早期细胞病理诊断系统0对肺癌细胞涂片诊断率高,克服了肺癌细胞病理诊断过程中取检细胞数量少,重叠细胞识别率低,涂片背景及染色差异等干扰因素,可辅助临床肺部病灶的穿刺细胞病理诊断"-Objective Design and develop a intelligent cytopathological lung cancer diagnosing system(ICLCDS) utilizing the latest computer technologies(including Reinforcement Lcaming Multiple Classifier Fusion and Dimcnsionality Reduction) and the cy-topathological knowledge on lung canccrcclls Methods We got information ofcclls and segregated cell regions in a slice image using an magi scgmcntouon a址orithm Sascd on reinforcement lcaming including rcconstmction of overlapped cell area Sascd on B一Spline and improved dcBoor-Cox Mcthoc} We comSincd multiple classifiers including Baycsian classific:Support Vector Machine(SVM) classific K-Ncarcst NcighSour( KNN) and Decision c classific to achieve an accurate result of cytopathological lung cancer diag-nosis Results Experimental results on 1 200 cases randomly selected we as follows the accurate diagnosis rate for lung cancer idcn-tification was the false positive rate was 1. 8`J /c‘the false negative rate was 3. 3`J /c‘the type class
Update : 2025-02-17 Size : 216kb Publisher : 高阳