1) binary domain
二值域
1.
The problem two fewer and one more in information hiding was transformed to find the solution vector,which had the least weight,of the nonhomogeneous linear equations whose elements amount wasn t fixed,on binary domain,built a mathematical model,and gave the solution models.
将信息隐藏中的两少一多问题转换为求二值域上变量元数不确定的非齐次线性方程组的最小权值解向量,构建了一个数学模型,对模型进行求解,作为问题模型的解给出了答案模型。
2) quadratic numerical range
二次数值域
1.
The quadratic numerical range of a class of unbounded infinite dimensional Hamiltonian operators are studied.
研究了一类无界无穷维Hamilton算子的二次数值域的性质,进而,应用二次数值域来刻画了无穷维Hamilton算子谱的分布范围,并给出了二次数值域的闭包包含谱集的结论。
3) time-binaryzation
时域二值化
1.
Based on analysis and comparative study in binaryzation of fixed threshold,semi-adaptive threshold and auto-adaptive threshold, the time-binaryzation algorithm is proposed.
针对三维测量中条纹图像序列的特点,对固定阈值、准自适应阈值和自适应阈值的二值化方法进行深入分析和对比研究,提出了利用图像差影实现时域二值化的算法。
4) quadratic numerical range
二次数值值域
1.
In this paper,we discuss the quadratic numerical range of the restriction Γ to M, the quadratic numerical range of finitely direct sum of Γ, the relation of the quadratic numerical range with invariant subspace.
讨论了Γ对M限制的二次数值值域 ,Γ的有限直和的二次数值值域及Γ的二次数值值域与不变子空间的关系。
5) local binary pattern
局域二值模式
1.
The local binary pattern was introduced to extract the texture feature.
引入局域二值模式(LBP)算子提取纹理特征,利用颜色直方图与纹理直方图相似度的加权和表示目标相似度,以有效解决自遮挡对跟踪的影响。
2.
First,locate the eyes automatically with the method of geometrical matching;then the Local Binary Pattern(LBP) operator is used to extract face appearance features;finally a two-stage classification method is proposed.
该方法首先采用几何模型匹配法自动定位出人眼,在此基础上进行人脸大小归一化,然后利用局域二值模式(LocalBinaryPattern,LBP)技术提取面部特征,最后采用由粗到细的方案进行表情分类。
3.
The highlights and main contributions of the dissertation include:(1)An age estimation algorithm based on selected Local Binary Pattern and weighted Support Vector Machine regression is proposed.
本文的工作主要包括:(1)提出基于优选局域二值模式与加权支持向量机回归相结合的年龄估计方法。
6) linear maps preserving the quadratic numerical range
线性保二次数值值域
补充资料：[1,1'-双(二苯基膦)二茂铁]二氯化钯二氯甲烷络合物
分子式：C35H30Cl4FeP2Pd
分子量：816.64
CAS号：95464-05-4
性质：
分子量：816.64
CAS号：95464-05-4
性质：
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条