一种基于步幅长度及频域特征的步态识别方法

步态识别作为一种较新的生物认证技术有其独特优势,它旨在根据人行进过程中的行走步态模式来识别其身份.提出一种基于步幅长度及频域特征的步态识别方法:首先采用背景减除算法实现运动人体检测,并根据步幅长度变化特征进行周期分割.然后提取步幅长度极值结合关键帧的频幅均值构成五维特征向量,最后用标准模式分类器在中科院自动化所提供的CASIA步态数据库中进行实验,在降低了算法复杂度的同时,获得了令人鼓舞的实验结果.     

基于行为特征识别的网络诈骗嫌疑人追踪系统

在互联网日益发展的今天,网络诈骗随时随处都在发生,犯罪嫌疑人的身份极难识别,给网络诈骗案件的侦破带来了困难。文章以即时聊天工具QQ为例,对网络诈骗嫌疑人身份识别及追踪给出一个完整的解决方案。文章的思路是通过行为特征来进行嫌疑人的身份识别,行为特征指不同人的击键特征,能够高精准地区分不同的人,而且键盘普及率很高,这给系统运行提供了硬件环境。在系统中,文章通过监听用户键盘击键进行击键特征提取,并且引入本地验证和服务器验证对用户进行身份识别,通过IP对疑犯进行定位,从而协助执法人员进行网络诈骗案件的侦查。     

油酸二聚甘油酯的合成及其柔软保湿纸的测试

以油酸缩水甘油酯和甘油为原料，在固体酸催化剂（活性炭负载硫酸）作用下，通过开环反应制得油酸二聚甘油酯。通过FTIR和1HNMR对产物结构进行表征，并将其用作柔软保湿剂涂覆到面巾纸上对纸张的柔软度、保湿性、抗张强度等性能进行测试。结果表明：油酸二聚甘油酯具有优异的柔软保湿性能，在油酸二聚甘油酯添加量为甘油水溶液质量的0.25%时，面巾纸的柔软度（49 mN）优于市面上有机硅柔软剂改性的面巾纸柔软度（68 mN），这是由于大分子柔软剂能够对纤维表面的缺陷进行修复，从而使纤维表面平整度的提升。且在温度为30 ℃，湿度为60%时，油酸二聚甘油酯型柔软保湿剂涂覆后的面巾纸的保水率（98.2%）也略高于有机硅柔软剂涂覆后的面巾纸的保水率（96.5%）。     

基于流形学习的整体正交稀疏保留鉴别分析

稀疏保留投影是一种有效的特征提取方法,但是其主要关注样本间的全局稀疏重构关系,并且得到的投影变换通常不是正交的。在实际应用中,图像数据往往处于高维空间中的一种低维流形中,正交性一直被认为有利于提高鉴别能力。文中以有监督学习的方式在稀疏保留投影中引入了流形结构保留,并使得投影空间正交,从而提出了一种新的特征提取方法,即基于流形学习的整体正交稀疏保留鉴别分析（MLHOSDA）。在人脸和掌纹图像数据库的实验结果表明此方法具有较好的识别效果。     

Feature selection on probabilistic symbolic objects

In data analysis tasks, we are often confronted to very high dimensional data. Based on the purpose of a data analysis study, feature selection will find and select the relevant subset of features from the original features. Many feature selection algorithms have been proposed in classical data analysis, but very few in symbolic data analysis （SDA） which is an extension of the classical data analysis, since it uses rich objects instead to simple matrices. A symbolic object, compared to the data used in classical data analysis can describe not only individuals, but also most of the time a cluster of individuals. In this paper we present an unsupervised feature selection algorithm on probabilistic symbolic objects （PSOs）, with the purpose of discrimination. A PSO is a symbolic object that describes a cluster of individuals by modal variables using relative frequency distribution associated with each value. This paper presents new dissimilarity measures between PSOs, which are used as feature selection criteria, and explains how to reduce the complexity of the algorithm by using the discrimination matrix.     

An algorithm and observability research of autonomous navigation and joint attitude determination in asteroid exploration descent stage

In this paper, an autonomous relative navigation and joint attitude determination algorithm in asteroid exploration descent stage is researched based on feature point information of perpendicular asteroid surface image observed by optical navigation camera, distance vectors from spacecraft to asteroid measured by three angled installed lidars and relative velocity increment measured by accelerometer when the relative distance vector to the centroid of asteroid can not be obtained. The inertial attitude of spacecraft is determined by sun vector, star vectors and inertial angular velocity respectively measured by sun sensor, star trackers and inertial reference unit. Also, in order to obtain measurement error model transferred from sensor noise, a covariance matrix solver considering error correlation is presented via the error model of normalized vector to first order. Numerical simulation and improved observability evaluation of filtering are undertaken to discuss the results of complete sensor observation and weak observation of lidars, and verify the effectiveness of the presented relative navigation and attitude determination algorithm.     

Local adaptive segmentation algorithm for 3-D medical image based on robust feature statistics

Medical image segmentation is of pivotal importance in computer-aided clinical diagnosis. Many factors, including noises, bias field effect, local volume effect, as well as tissue movement may affect the med- ical image, thus causing blurring or uneven characteristics when forming a picture. Such quality defects will inevitably impair the gray-scale difference between adjacent tissues and lead to insufficient segmentation or even leakage during tissue or organ segmentation. In the present investigation, a local adaptive segmentation algorithm for 3-D medical image based on robust feature statistics （LARFS） was proposed. By combining segmentation algorithm principles for traditional region growing （RG） and robust feature statistics （RFS）, the location and neighborhood image information of input seed point can be comprehensively analyzed by LARFS. Results show that, for different segmentation objects, under controlling the input parameter of growing factor within certain range, LARFS segmentation algorithm can adapt well to the regional geometric shape. And be- cause the robust feature statistics is applied in the contour evolution process, LARFS algorithm is not sensitive to noises and not easily influenced by image contrast and object topology. Hence, the leakage and excessive segmentation effects are ameliorated with a smooth edge, and the accuracy can be controlled within the effective error range.     

焙烧高岭土的结构特征和吸附性能

通过对焙烧高岭土的矿物特性和表面吸附性质的研究。用化学分析，ＸＲＤ、ＩＲ、ＸＰＳ、Ｒａｍａｎ光谱和ＳＥＭ观察证明焙烧高岭土的羟基基团完全消失，等温吸附，粒度分布试验证明焙烧高岭土水化能力较大，但吸附能力较弱。     

基于注意力和卷积特征重排的图像修复

近年来,基于UNet与GAN（生成对抗网络）的深度学习网络模型在图像修复领域展现出了独特的优势,但是修复结果中仍然存在伪影、模糊、纹理细节退化、对于大面积破损难以修复、修复后的孔洞与背景图像不相容等现象。为了解决现有模型对大面积破损图像修复不友好以及修复后的图像存在退化现象等问题,通过对现有方法进行研究,改进了Shift-UNet（移位网络）模型：在UNet与GAN的基础上,在每一层编码器和解码器之间增加了改进之后的注意力机制Attention-UNet并融入shift-UNet,形成Attention-Shift-UNet;并且通过研究,将原来下采样部分的激活函数由Leaky_ReLU改为了SiLU函数。改进模型不仅在64×64的中心遮罩上取得了较好的效果,还实现了随机遮罩,遮罩面积由20%增加到80%。通过实验结果证明,该模型的修复效果更优,特别是针对大面积破损图像的修复。在CelebA、ParisArchitecture以及Paris Streetview数据集上经过测试,各评价指标都有明显的提高,其中结构相似性（SSIM）由原来的0.944 5提高到0.947 1,峰值信噪比（PSNR）由原来的27.992 7提高到28.553 6,L2损失由原来的0.001 7降低到0.001 5。     

基于知识回顾与特征解耦的目标检测蒸馏

当前的知识蒸馏算法均只在对应层间进行蒸馏,为了解决这一问题,提高知识蒸馏的性能,首先分析了教师模型的低层特征对学生模型高层特征的指导作用,并在此基础上提出了基于知识回顾解耦的目标检测蒸馏方法。该方法首先将学生模型的高层特征与低层特征对齐、融合并区分空间和通道提取注意力,使得学生的高层特征能够渐进式地学到教师的低层和高层知识;随后将前背景解耦,分别蒸馏;最后通过金字塔池化在不同尺度上计算其与教师模型特征的相似度。在不同的目标检测模型上进行了实验,实验表明,提出的方法简单且有效,能够适用于各种不同的目标检测模型。骨干网络为ResNet-50的RetinaNet和FCOS分别在COCO2017数据集上获得了39.8%和42.8%的mAP,比基准提高了2.4%和2.3%。