身份保持约束下的面部图像超分辨率重建方法

低分辨率是影响人脸识别精度的重要因素。一种有效方法是使用图像超分辨率技术对低分辨率图像重建,生成超分辨率图像后再对其作人脸识别,从而克服低分辨率面部图像对人脸识别的限制。但是,现有超分辨率方法在重建过程中往往忽略了保持其原始身份信息,这直接影响生成图像的人脸识别结果。针对上述问题,提出了一种身份保持约束下的面部超分辨率重建方法IPNet,在提高低分辨率面部图像质量的同时,能保持重建后的面部图像身份。IPNet方法将语义分割网络和面部生成器相结合,通过语义分割网络提取低维隐码和多分辨率空间特征,进而指导面部生成器输出接近于原图的真实面部图像。在此基础上引入人脸识别网络,将身份信息整合到超分辨率方法中,从而约束重建前后的面部图像身份保持一致。实验结果表明,IPNet方法在超分辨率图像质量和身份保持上均优于其他对比方法。     

基于多尺度圆周频率滤波与卷积神经网络的遥感图像飞机目标检测方法研究

针对遥感图像飞机目标检测因目标尺度不一存在漏警、虚警等问题,该文基于遥感图像中飞机目标形状特征和灰度变化特点提出了一种多尺度圆周频率滤波(MSCFF)与卷积神经网络(CNN)相结合的MSCFF+CNN飞机目标自动检测算法.该算法首先采用多尺度圆周频率滤波器滤除遥感图像复杂背景,实现不同尺度飞机目标候选区域提取;然后,通过构建卷积神经网络(CNN)模型实现候选区域有效分类,最终精确确定飞机目标位置.最后,基于获取的真实遥感图像进行目标检测算法实验验证,经统计该算法的飞机目标检测率为94.38%,虚警率为3.76%,实验结果充分验证了该文算法的有效性,该算法可为机场监管、军事侦察等应用提供重要的技术支持.     

圆环式径向换能器声压分布及其指向性

根据圆环式径向换能器的对称性,定性分析了其声压分布性质,提出将辐射面镶在无限幕上并向辐射面的外法线所在的半空间辐射声场的分析模型;根据惠更斯原理,推导了圆环式径向换能器辐射声场远场区的声压分布以及指向性函数;通过MATLAB绘制指向性函数曲线,研究换能器的有效工作段长度、外径以及辐射频率对其指向性的影响。结果表明,当换能器的尺寸一定时,辐射频率增大,指向性增强;当换能器的辐射频率和外径一定时,换能器的有效工作段长度增大,指向性增强;当换能器的辐射频率和有效工作段长度一定时,外径对声场指向性的影响不大。结合有限元分析软件COMSOL Multiphysics,仿真声波在混凝土中的传播,进一步验证了以上结论。     

A simple spatial integration scheme for solving Cauchy problems of non-linear evolution equations

In this study, we address a new and simple non-iterative method to solve Cauchy problems of non-linear evolution equations without initial data. To start with, these ill-posed problems are analysed by utilizing a semi-discretization numerical scheme. Then, the resulting ordinary differential equations at the discretized times are numerically integrated towards the spatial direction by the group-preserving scheme (GPS). After that, we apply a two-stage GPS to integrate the semi-discretized equations. We reveal that the accuracy and stability of the new approach is very good from several numerical experiments even under a large random noisy effect and a very large time span.     

谐振子的辛欧拉分析方法

针对理想简谐振子力学模型,研究了其守恒律,并利用辛欧拉格式分析简谐振子振动过程.首先给出了谐振子系统的平方守恒律、周期守恒律和相差守恒律.构造了谐振子的普通欧拉格式和辛欧拉格式,研究了两种格式下三种守恒律各自的保持情况.模拟结果显示:辛欧拉格式能够精确保持时域守恒律(平方守恒律),但无法保持频域守恒律(周期守恒律和相差守恒律).如要克服辛欧拉格式的不足,需按邢誉峰教授提出的方法进行校正.     

对称循环矩阵的一些结果

讨论了对称循环矩阵的性质,并研究了任意矩阵在对称循环矩阵中的逼近问题。     

Quasi-physical global optimization method for solving the equal circle packing problem

The equal circle packing problem is a well-known challenge in geometry.It is also a natural,clear and fair test system for global optimization.This paper presents a quasi-physical global optimization algorithm for solving the equal circle packing problem.The algorithm simulates two kinds of movements of N elastic disks: smooth movement driven by elastic pressures and violent movement driven by strong repulsive forces and attractive forces.The smooth movement makes the disks reach a locally optimal configura...     

LPP solution schemes for use with face recognition

Locality preserving projection (LPP) is a manifold learning method widely used in pattern recognition and computer vision. The face recognition application of LPP is known to suffer from a number of problems including the small sample size (SSS) problem, the fact that it might produce statistically identical transform results for neighboring samples, and that its classification performance seems to be heavily influenced by its parameters. In this paper, we propose three novel solution schemes for LPP. Experimental results also show that the proposed LPP solution scheme is able to classify much more accurately than conventional LPP and to obtain a classification performance that is only little influenced by the definition of neighbor samples.     

On minimum class locality preserving variance support vector machine

In this paper, a so-called minimum class locality preserving variance support machine (MCLPV_SVM) algorithm is presented by introducing the basic idea of the locality preserving projections (LPP), which can be seen as a modified class of support machine (SVM) and/or minimum class variance support machine (MCVSVM). MCLPV_SVM, in contrast to SVM and MCVSVM, takes the intrinsic manifold structure of the data space into full consideration and inherits the characteristics of SVM and MCVSVM. We discuss in the paper the linear case, the small sample size case and the nonlinear case of the MCLPV_SVM. Similar to MCVSVM, the MCLPV_SVM optimization problem in the small sample size case is solved by using dimensionality reduction through principal component analysis (PCA) and one in the nonlinear case is transformed into an equivalent linear MCLPV_SVM problem under kernel PCA (KPCA). Experimental results on real datasets indicate the effectiveness of the MCLPV_SVM by comparing it with SVM and MCVSVM.     

基于NPDM的保障系统顶层数据模型研究

介绍了北约产品数据模型(NPDM)的三层体系结构和EXPRESS数据建模语言,着重分析了NPDM顶层数据模型与产品寿命周期的关系,模型中各模式记录的信息内容和模式之间的关系.依据NPDM思想建立了保障系统顶层数据模型,阐述了模型中各模式记录的信息内容,给出了人力与人员、保障设备和保障设施等保障要素的数据结构,为进一步建立保障系统数据模型的打下了基础.