ransac造句

• In line and ellipse detection, a robust algorithm based on zom edge detection, rht and k-ransac is presented
  本论文研究了基于zom边缘提取和rht的直线和k-ransac椭圆基元的提取算法。
• After the arrangement information has been obtained, the ransac method is used to get rid of false matches in the second phase matching
  获得了图像序列位置关系后,自动拼接算法进行第二个阶段的特征匹配,这一个阶段使用了ranasac算法提纯粗略匹配数据。
• The thesis is focused on above associated issues . ransac algorithm is a classical method of robust model parameter estimation . a preview model parameters evaluation ransac ( peransac ) algorithm is developed, which introduces a preview model parameters evaluation in the ransac algorithm, and results in better performance since the worse contaminated samples are discarded with guaranteeing the same confidence as ransac
  随机抽样一致性(ransac)算法是一个经典的鲁棒性模型参数估计方法,本文提出了基于预检验的快速随机抽样一致性(peransac)算法,通过对模型参数预检验,在保证计算结果置信度的基础上,删除明显错误的模型参数,减少参与检验的模型参数数量,进而提高算法的整体效率。
• The thesis is focused on above associated issues . ransac algorithm is a classical method of robust model parameter estimation . a preview model parameters evaluation ransac ( peransac ) algorithm is developed, which introduces a preview model parameters evaluation in the ransac algorithm, and results in better performance since the worse contaminated samples are discarded with guaranteeing the same confidence as ransac
  随机抽样一致性(ransac)算法是一个经典的鲁棒性模型参数估计方法,本文提出了基于预检验的快速随机抽样一致性(peransac)算法,通过对模型参数预检验,在保证计算结果置信度的基础上,删除明显错误的模型参数,减少参与检验的模型参数数量,进而提高算法的整体效率。
• The thesis is focused on above associated issues . ransac algorithm is a classical method of robust model parameter estimation . a preview model parameters evaluation ransac ( peransac ) algorithm is developed, which introduces a preview model parameters evaluation in the ransac algorithm, and results in better performance since the worse contaminated samples are discarded with guaranteeing the same confidence as ransac
  随机抽样一致性(ransac)算法是一个经典的鲁棒性模型参数估计方法,本文提出了基于预检验的快速随机抽样一致性(peransac)算法,通过对模型参数预检验,在保证计算结果置信度的基础上,删除明显错误的模型参数,减少参与检验的模型参数数量,进而提高算法的整体效率。
• The thesis is focused on above associated issues . ransac algorithm is a classical method of robust model parameter estimation . a preview model parameters evaluation ransac ( peransac ) algorithm is developed, which introduces a preview model parameters evaluation in the ransac algorithm, and results in better performance since the worse contaminated samples are discarded with guaranteeing the same confidence as ransac
  随机抽样一致性(ransac)算法是一个经典的鲁棒性模型参数估计方法,本文提出了基于预检验的快速随机抽样一致性(peransac)算法,通过对模型参数预检验,在保证计算结果置信度的基础上,删除明显错误的模型参数,减少参与检验的模型参数数量,进而提高算法的整体效率。