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One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent compa...
This paper focuses on backscattering mechanisms selection and supervised classification works for CETC38-X PolSAR image. Thanks to the high radar resolution, many classes of man-made objects are vis...
Traditional geometry-based approach can maintain the characteristics of vector data. However, complex interpolation calculations limit its applications in high resolution and multi-source spatial da...
In this paper, a novel formulation, smooth entropy support vector regression (SESVR), is proposed, which is a smooth unconstrained optimization reformulation of the traditional linear programming asso...
Support vector machine (SVM) is a popular pattern classification method with many application areas. SVM shows its outstanding performance in high-dimensional data classification. In the process of cl...
This document presents an approach using the maximum likelihood formulation to estimate vector velocities in real-time by a network of Doppler radars. Relationships between the estimated vector veloci...
this paper presents the basics of information retrieval: the vector space model for document representation with Boolean and term weighted models, ranking methods based on the cosine factor and evalua...
针对虚拟场景中大规模人群图像绘制时由于采集图像数量有限,在视点连续变化时出现跳变的问题,提出了一种基于Motion Vector的图像绘制算法,该算法通过移动原始图像的像素位置生成相邻视点位置的图像,使得各个离散采样之间能够连续过渡,很好地解决了由于采样不足而引起的跳变问题,同时保证了绘制系统的实时性,实验结果验证了该算法的有效性。
This paper proposes a new multi-class support vector machine for simultaneous gene selection and microarray classification. Combining the huberized hinge loss function and the elastic net penalty, the...
利用闭凸集上的投影解释support vector的几何意义,利用支持超平面讨论线性分类器 的设计问题.对线性可分情形,Support vector由一类数据集合闭凸包在另一类数据集合闭凸包上投影的非零系数向量组成,SVM所决定的超平面位于两投影点关于各自数据集合支持超平面的中间.作为应用,文中给出一种设计理想联想记忆前馈神经网络的方法,它是FP算法的一般化.
In this paper, we propose a novel hybrid de-interlacing algorithm, which effectively combines two motioncompensated (MC) de-interlacing techniques: MC Median Filtering (MCMF) and Adaptive Recursive (A...
Feature extraction, discriminant analysis, and classification rules are three crucial issues for face recognition. This paper presents method, named GaborfaceSVM, to handle three issues together. For...

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