A sliding window technique for interactive high-performance computing scenarios

Interactive high-performance computing is doubtlessly beneficial for many computational science and engineering applications whenever simulation results should be visually processed in real time, i.e. during the computation process. Nevertheless, interactive HPC entails a lot of new challenges that have to be solved – one of them addressing the fast and efficient data transfer between a simulation back end and visualisation front end, as several gigabytes of data per second are nothing unusual for a simulation running on some (hundred) thousand cores. Here, a new approach based on a sliding window technique is introduced that copes with any bandwidth limitations and allows users to study both large and small scale effects of the simulation results in an interactive fashion.     

无线传感器网络中目标跟踪的马尔可夫模型与预测方法

针对目标运动是一个包含许多不确定因素的非线性非高斯随机过程,提出基于马尔可夫随机场模型与粒子滤波的WSN分布式目标跟踪方法(MRF-PF)。把目标跟踪过程看作是一个马尔可夫过程,基于贝叶斯规则,建立目标状态分布函数,用粒子滤波估计目标状态,实现目标跟踪。实验结果:对于泊松白噪声,MRF-PF方法的跟踪均方根误差RMSE相比卡尔曼滤波(KF)和扩展卡尔曼滤波(EKF)方法分别降低52.6%、49.2%;对于方差σ2由0.3→3的高斯噪声,GM-PF方法的RMSE相比KF、EKF分别降低54.5%～77.2%和23.5%～54.2%。这表明MRF-PF方法在非线性非高斯噪声或高斯噪声变化较大时具有较好的抗噪能力及跟踪性能。     

基于图论优化的块采样纹理合成

基于马尔可夫随机场(MRF)模型和已有的块采样合成技术,提出一种改进的合成算法,采用图论的最小割线算法对MRF的似然性进行优化,将合成时的光栅扫描方式改为之字形扫描方式,以抑制纹理的倾向性和纹元的不完整性。试验证明,该算法的合成效果较好。     

基于MRF-MAP的运动矢量恢复差错掩盖算法

针对帧间编码模式下出现图像块丢失的情况,提出一种有效的时间域运动矢量恢复差错掩盖算法。把运动矢量场建模为高斯马尔科夫随机场,对丢失图像块的运动矢量采用最大后验概率方法恢复,其权值能够根据空间和时间信息而自适应选择。仿真结果表明,该算法在客观和主观上都能获得高质量的图像。     

基于二代bandelets域HMT模型的图像分割

在小波域隐马尔可夫树模型(WHMT)图像分割算法的基础上,根据二代handelets系数的分布统计特性,提出一种新的bandelets域隐马树模型(BHMT)有监督图像分割算法.新算法试图利用二代bandelets能表示图像几何规律性的特点来改进分割效果.为证明算法的有效性,用合成纹理图像和真实的航空和遥感图像做分割实验,并和小波域隐马模型树分割算法作了对比,对合成纹理图像分割,用错分概率作为评价参数.实验结果表明,此方法错分概率低、分割效果理想.     

数字图像超分辨率重建技术综述

图像超分辨率重建的目的是通过一幅或多幅低分辨率降质图像来估计一幅视觉效果较好的高分辨率图像.它从传统的图像恢复与重建技术而来,利用图像之间的信息互补来获得比单幅图像更多的细节.超分辨率技术主要分为两大类:基于重建的超分辨率技术和基于学习的超分辨率技术.基于重建的超分辨率技术按照特定的退化模型,通过输入的图像来估计高分辨率图像.基于学习的超分辨率技术从训练样本中获取先验知识,对输入图像的信息进行补充,可以获得比基于重建的算法更好的效果.对超分辨技术的算法作了系统的介绍,并指出图像的配准、退化模型的建立、盲估计问题、学习模型的建立、学习算法等仍是图像超分辨率技术中存在的主要问题,也是进一步研究的方向.     

马尔可夫随机场在显微图像散焦深度信息估计中的应用

针对显微视觉图像深度信息估计问题,提出了一种基于马尔可夫随机场的散焦特征参数模型;该模 型将散焦特征深度信息的估计转化为能量函数的优化问题．应用迭代条件模式（Iterated Conditional Mode,ICM） 算法进行优化,在ICM 算法中应用最小二乘估计（LSE）算法对初始点参数进行估计,从而改进了ICM 算法的性 能,防止了其进入局部最优解．实验与仿真证实了该模型和算法的有效性和可行性．     

基于小波变换的含噪人耳图像边缘检测

为了取得含噪人耳图像的理想边缘轮廓,以实现人耳识别技术的进一步应用,对小波变换边缘检测方法进行了研究,分析了噪声消除与小波变换尺度之间的关系,详细论述了模局部极大值提取边缘的原理.针对含噪人耳图像的特殊性,阐述了一般去噪和边缘检测方法的不足,并针对这些不足提出了改进方法,首先利用样条小波多尺度分解后,相邻尺度小波系数相乘得到尺度积,然后进一步求得尺度积的模和相角,通过自适应阈值去噪提取图像边缘,取得了较好效果.     

A Multi-scale Attention-based Facial Emotion Recognition Method Based on Deep Learning

Recently, people have been paying more and more attention to mental health, such as depression, autism, and other common mental diseases. In order to achieve a mental disease diagnosis, intelligent methods have been actively studied. However, the existing models suffer the accuracy degradation caused by the clarity and oc-clusion of human faces in practical applications. This paper, thus, proposes a multi-scale feature fusion network that obtains feature information at three scales by locating the sentiment region in the image, and integrates global feature information and local feature information. In addition, a focal cross-entropy loss function is designed to improve the network''s focus on difficult samples during training, enhance the training effect, and increase the model recognition accuracy. Experimental results on the challenging RAF_DB dataset show that the proposed model exhibits better facial expression recognition accuracy than existing techniques.     

Weave geometry generation avoiding interferences for mesoscale RVEs

An algorithm which allows the generation of representative volume elements (RVEs) for complex woven and warp-interlaced fiber-reinforced composite topologies while avoiding unphysical tow intersections is presented. This is achieved by extending an existing RVE generation strategy in two significant ways: (1) the local cross section shape of the tow is adjusted depending on the local tow curvature in a way that preserves the cross sectional area of the tow, and (2) the elementary crimp interval is separated into a planar and a transition region. The modifications facilitate the generation of a wide range of elaborate textile topologies without tow intersections, which are present without the proposed modifications unless complex tow to tow contact models are introduced. The mechanical properties of plain weaves were predicted based on the topology generated with the proposed algorithm as well as based on RVEs which were constructed based on actual micrographs, i.e. a “digital twin” of the actual microstructure. A comparison of the predicted mechanical properties based on finite element and Multiscale Generalized Method of Cells techniques shows close agreement. However, some differences exist with respect to experimentally determined material parameters due to the finite dimensions of the specimens. Lastly, mechanical properties of multilayered weaves are predicted with the finite element method. The considered material systems are carbon fiber in epoxy matrix as well as C/C-SiC. However, the procedure is applicable to a wide range of material systems.