提出一种基于基线和中心点的电场模型，用于估计指纹方向场。
An electric field model based on baseline and core points is proposed to estimate fingerprint orientation field.
提出了一种利用隐马尔可夫模型(HMM)和支持向量机(SVM)的两级指纹分类新方法。
A new two-stage method of fingerprint classification is proposed that is based on hidden Markov model (HMM) and support vector machine (SVM).
选择被受到的影响和密码经理和植入的安全次要系统装备整合的指纹读者的T43 的模型。
Select models of the T43 come equipped with the integrated fingerprint reader with Password Manager and the Embedded Security Subsystem.
目的从先天性巨结肠(HD)患儿血清蛋白质中筛选特异的蛋白质标记物，构建诊断HD的血清蛋白质指纹图谱模型。
Objective To set up a model for the detection of the serum protein by using the protein chip technology for exploration of serum protein finger print pattern models in Hirschsprung's Disease (HD).
本文提出了一种改进的指纹纹线方向场计算方法，其中重点分析了奇异点模型中旋转角度的估计方法，并在复数域内简化了纹线方向场的优化计算。
This paper introduces an improved algorithm for fingerprint direction field estimation, the rotation angle estimation during constructing the singular point models is analyzed in details.
目的：建立直肠癌筛选血清蛋白质指纹图谱模型并初步验证。
AIM: To establish a serum protein pattern model for screening rectal carcinoma.
目的：建立基于人工神经网络的血清蛋白质指纹图谱模型，并探讨其在肝癌诊断中的应用。
Aim: To evaluate the application of serum protein fingerprint pattern based on artificial neural network in diagnosis of liver cancer.
模型中利用了指纹的全局信息来调整网格点的值，使得它与传统的基于局部信息的方向场算法有本质的区别。
The orientation of grid points is adjusted by global information of the fingerprint, which is much different from the conventional method.
区分肾母细胞瘤与其他腹腔实体肿瘤的血清蛋白质指纹图谱模型特异性为100%，敏感性为93.3%。
The diagnostic model combined with 2 biomarkers could separate nephroblastoma from other child′s abdominal solid tumors with a sensitivity of 93.3%, and a specificity of 100%.
该算法主要包括三个特色技术：基于纹线局部走向的分类预测、体现指纹微观纹理的扩展上下文以及基于成像仪器的分类熵编码器概率模型初始化。
There are mainly three distinguishing features in our proposed algorithm:local direction-based prediction, extended context for micro texture and histogram initialization based on imaging apparatus.
离线阶段，通过在参考点上测量信号得到信号覆盖图，建立模型并存储位置指纹信息；
During the off-line phase, the system tabulates the signal strength received from the access points, stores fingerprint information and establish the model;
离线阶段，通过在参考点上测量信号得到信号覆盖图，建立模型并存储位置指纹信息；
During the off-line phase, the system tabulates the signal strength received from the access points, stores fingerprint information and establish the model;
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