视觉传感器网络协作块压缩感知图像传输方法

JPEG2000等现有图像压缩传输算法虽然压缩性能好,但复杂度高,资源受限的视觉传感器节点很难适应.基于压缩感知理论研究视觉传感器网络环境下的图像传输问题.首先设计主-从节点对模型,分块监测图像;然后研究协作块压缩感知理论,基于图像分块和节点协作来减少测量矩阵的维数,降低压缩感知的计算复杂度;对处在发送端的主从节点,提出尽力而为的压缩感知测量值传输方法,以最大化图像重构质量为目标,尽力传送最多的测量值;而在接收端,汇聚节点依据内积准则来判断重构质量,确定传输终止条件,避免多余的测量值传输,节省传输耗能.实验结果表明,和经典压缩感知相比较,4个视觉传感器节点协作的块压缩感知传输方法将测量矩阵维数减少了2个量级,且有更少的网络耗能.     

面向行人检测的异构视觉传感网络自适应标定

异构视觉传感网络的标定是实现准确行人检测、跟踪、识别以及行为分析的关键和前提,对公共安全和智能安防具有重要意义。本文提出了一种面向行人检测的异构视觉传感网络自适应标定方法。首先,构建主动旋转变焦(PTZ)传感节点变焦成像模型,采用基于SURF特征点匹配的方法实现内参数自标定。其次,构建外参数分布式标定模型,将异构视觉传感网络外参数标定分解为节点局部标定和网络全局标定,从而避免采用单一中心节点进行集中式处理,提高方法的可扩展性;最后,为了提高标定精度,采用自适应混沌微粒群优化算法最小化内、外参数估计的再投影误差和轨迹匹配误差。实验结果表明,本方法有效降低了网络通讯量和标定误差,提高了异构视觉传感网络行人检测精度,具有重要的理论和实际应用价值。     

梯度向量直方图的行人检测

行人是道路交通的参与者也是受害者,计算机视觉的行人检测,由于其在车辆辅助驾驶系统中的重要应用价值,成为当前计算机视觉和智能车辆领域最为活跃的研究课题之一。为了快速准确地对行人进行检测,提出了一种梯度向量直方图的行人检测方法。该方法使用高斯平滑进行图像预处理,然后利用直方图相似性,选择一些具有强分辨能力的特征来表征行人,最后用(Haar)特征分类器,从目标和背景中获得的经过筛选的特征。实验结果表明,该方法对行人检测是快速且有效的。     

无线传感网基于邻居簇的JPEG2000多节点协同实现

针对无线传感器网络能量、存储、处理能力严重受限的特点,基于"在网计算"的思想,结合JPEG2000算法流程以及无线传感器网络的网络拓扑结构特点,提出一种基于邻居簇的JPEG2000多节点协同图像压缩方法。首先,将相机节点采集的图像分片,并根据图像的梯度幅度值进行压缩比特率的自适应优化分配。然后,将压缩任务转移到多个邻居簇内,以最小化网络总能耗为目标,由多节点协作共同完成图像压缩和传输。仿真结果表明,该方法不仅使无线传感器网络中实现大尺寸图像的JPEG2000编码成为可能,且相机节点能耗仅为压缩图像后传输至基站方案的3.4%,极大地平衡了网络节点能耗,使网络生命周期提高了7倍以上。     

层次分簇的无线传感网络多级优化测量

层次化的无线传感网络由骨干传感节点和普通传感节点组成.由于节点能量受限,无线传感网络跟踪测量目标时需同时考虑目标跟踪精度和跟踪方法的能效性.提出一种层次分簇的多级优化无线测量方法.将骨干节点作为簇首,采用粒子滤波算法预测运动目标位置,运用DELAUNAY三角剖分优化选择目标附近的节点作为测量节点,并根据测量节点地理位置判断是否转移簇首.在测量节点同步的感知目标后,簇首利用熵来逐次选择能效性最高的测量节点数据进行融合,实现目标定位测量.试验表明,该方法能满足目标跟踪精度,并可有效的减少网络能耗,提高无线传感网络测量使用寿命.     

基于多模态特征融合的自主驾驶车辆低辨识目标检测方法#br#

针对自主驾驶车辆在真实驾驶环境下对低辨识目标的识别问题,提出了基于多模态特征融合的目标检测方法。基于Faster R-CNN算法设计多模态深度卷积神经网络,融合彩色图像、偏振图像、红外图像特征,提高对低辨识目标的检测性能;开发多模态（3种）图像低辨识度目标实时检测系统,探索多模态图像特征融合在自动驾驶智能感知系统中的应用。建立了人工标注过的多模态（3种）图像低辨识目标数据集,对深度学习神经网络进行训练,优化内部参数,使得该系统适用于复杂环境下对行人、车辆目标的检测和识别。实验结果表明,相对于传统的单模态目标检测算法,基于多模态特征融合的深度卷积神经网络对复杂环境下的低辨识目标具有更好的检测和识别性能。     

基于多模态特征融合的自主驾驶车辆低辨识目标检测方法

针对自主驾驶车辆在真实驾驶环境下对低辨识目标的识别问题,提出了基于多模态特征融合的目标检测方法。基于Faster R-CNN算法设计多模态深度卷积神经网络,融合彩色图像、偏振图像、红外图像特征,提高对低辨识目标的检测性能;开发多模态(3种)图像低辨识度目标实时检测系统,探索多模态图像特征融合在自动驾驶智能感知系统中的应用。建立了人工标注过的多模态(3种)图像低辨识目标数据集,对深度学习神经网络进行训练,优化内部参数,使得该系统适用于复杂环境下对行人、车辆目标的检测和识别。实验结果表明,相对于传统的单模态目标检测算法,基于多模态特征融合的深度卷积神经网络对复杂环境下的低辨识目标具有更好的检测和识别性能。     

无线传感网络测量的目标预测动态能量优化

能量约束是无线传感网络实际应用的关键问题之一。针对无线传感网络测量的能效性问题,提出目标预测动态能量优化方法,采用粒子滤波算法对测量目标状态进行预测,通过动态唤醒无线传感节点延长节点睡眠时间节省节点能量。根据无线传感网络节点分布计算能力,运用分布式遗传模拟退火算法优化目标测量过程,使网络能耗最小化。重点讨论机动目标跟踪应用,实现目标位置预测、节点睡眠状态规划和测量节点优化选择,提出节省通信能量的中转节点路由方案。机动目标跟踪的仿真试验表明,目标预测动态能量优化方法能降低节点能耗,并提高无线传感网络的能量有效性。     

基于对数极坐标变换的中心视亚像素算法

为了利用仿生视觉中的碰撞时间参数实现主动避碰控制,对增强图像中心视目标物体区域进行了研究。首先,应用对数极坐标变换对视觉图像进行压缩变换,在变换中应用双三次插值对图像中心视区域进行亚像素增强;然后,对应用对数极坐标变换算法后图像的不同偏心率下的精度以及不同偏心率尺度下最小精度进行分析。实验结果表明应用变换算法后,图像数据得到了有效的压缩,中心视的目标物体图像仍得到了增强。     

基于正方形网格能量模型的能量均衡策略

延长网络生命周期是无线传感器网络的一个重要的目标。不均衡的能耗在很大程度上影响了网络生命周期。在正方形网格能量模型的基础上,使传感节点以一定的概率直接传输到基站节点或经过中继节点多跳传输到基站,提出基于能量均衡消耗的延长无线传感网络的生命周期的算法,并进行了相关的计算推导。     

Minimal Realization of Linear Graph Models for Multi-physics Systems

An engineering system may consist of several different types of components,belonging to such physical"domains"as mechanical,electrical,fluid,and thermal.It is t...     

INTEGRAL EQUATION METHOD＇S APPLICATION IN HOLE-EDGE STRESS OF COMPOSITE MATERIAL PLATE WITH DIFFERENT SHAPED HOLES

The strength of composite plate with different hole-shapes is always one of the most important but complicated issues in the application of the composite material. The holes will lead to mutations and discontinuity to the structure. So the hole-edge stress concentration is always a serious phenomenon. And the phenomenon makes the structure strength decrease very quickly to form dangerous weak points. Most partial damage begins from these weak points. According to the complex variable functions theory, the accurate boundary condition of composite plate with different hole-shapes is founded by conformal mapping method to settle the boundary condition problem of complex hole-shapes. Composite plate with commonly hole-shapes in engineering is studied by several complex variable stress fimction. The boundary integral equations are founded based on exact boundary conditions. Then the exact hole-edge stress analytic solution of composite plate with rectangle holes and wing manholes is resolved. Both of offset axis loadings and its influences on the stress concentration coefficient of the hole-edge are discussed. And comparisons of different loads along various offset axis on the hole-edge stress distribution of orthotropic plate with rectangle hole or wing manhole are made. It can be concluded that hole-edge with continuous variable curvatures might help to decrease the stress concentration coefficient; and smaller angle of outer load and fiber can decrease the stress peak value.     

Non-monotonic material contrast in scanning ion and scanning electron images

30 keV Ga⁺ focused ion beam induced secondary electron (iSE) imaging was used to determine the relative contrast between several materials. The iSE signal compared from C, Si, Al, Ti, Cr, Ni, Cu, Mo, Ag, and W metal layers does not decrease with an increase in target atomic number Z₂, and shows a non-monotonic relationship between contrast and Z₂. The non-monotonic relationship is attributed to periodic fluctuations of the stopping power and sputter yield inherent to the ion–solid interactions. In addition, material contrast from electron-induced secondary electron (eSE) and backscattered electron (BSE) images using scanning electron microscopy (SEM) also shows non-monotonic contrast as a function of Z₂, following the periodic behavior of the stopping power for electron–solid interactions. A comparison of the iSE and eSE results shows similar relative contrast between the metal layers, and not complementary contrast as conventionally understood. These similarities in the contrast behavior can be attributed to similarities in the periodic and non-monotonic function defined by incident particle–solid interaction theory.     

Application of Feature Extraction through Convolution Neural Networks and SVM Classifier for Robust Grading of Apples

This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,an...     

分布动态载荷识别的抗噪处理

针对正交多项式频域法在用多种响应对矩形薄板进行载荷识别中抗噪性较差的问题,综合运用平均法、矩阵预处理和奇异值截断法等方法对之进行改善,并引入空间映射的思想,将该方法的应用范围拓展为复杂的模型.利用仿真算例,证实了该方法具有较好的抗噪性.     

基于MELTAC-N平台的核电厂安全级DCS环网研究与测试

针对工程实践中环网通讯相关问题的处理缺乏理论基础及国产化安全级DCS平台的开发缺乏成熟经验借鉴问题,对基于MELTAC-N平台核电厂安全级DCS环网的软硬件实现进行了研究。提出了安全级DCS环网双环网冗余设计、光切换开关设计等硬件设计方法,以及以RPR协议为基础,采用全数据收发策略的软件设计方法。在CPR1000安全级DCS平台上对安全级DCS环网的可靠性及实时性进行了评价,并进行了容错能力、响应时间及响应时间稳定性测试验证实验。结果表明,基于MELTAC-N平台安全级DCS环网软硬件设计具有较好的容错能力及响应时间稳定性。     

Short-Term Relay Quality Prediction Algorithm Based on Long and Short-Term Memory

The fraction defective of semi-finished products is predicted to optimize the process of relay production lines, by which production quality and productivity ar...     

End-to-End Multiview Gesture Recognition for Autonomous Car Parking System

The use of hand gestures can be the most intuitive human-machine interaction medium.The early approaches for hand gesture recognition used device-based methods....     

The laboratory simulation of abrasive wear

Abrasive wear has long been recognised as one of the most potentially serious tribological problems facing the operators of many types of plant and machinery; several industrial surveys have indicated that wear by abrasion can be responsible for more than 50% of unscheduled machine and plant stoppages. Locating the operating point of a tribological contact in an appropriate operational ‚map’︁ can provide a useful guide to the likely nature and origins of the surface degradation experienced in use, though care must be exercised in choosing the most suitable parameters for the axes of the plot. Laboratory testing of materials and simulations of machine contacts are carried out for a number of purposes; at one level for the very practical aims of ranking candidate materials or surface hardening treatments in order of their wear resistance, or in an attempt to predict wear lives under field conditions. More fundamentally, tests may be aimed at elucidating the essential physical mechanisms of surface damage and loss, with the longer term aim of building an analytical and predictive model of the wear process itself. In many cases, component surface damage is brought about by the ingress of hard, particulate matter into machine bearing or sealing clearances. These may be running dry although, more usually, a lubricant or service fluid is present at the interface. A number of standardised wear test geometries and procedures have been established for both two- and three-body wear situations, and these are briefly described. Although abrasive wear is often modelled as following an ‚Archard’︁ equation (i.e. a linear increase in material loss with both load and time, and an inverse dependence on specimen hardness) both industrial experience and laboratory tests of particularly lubricated contacts show that this is not always the case: increasing the hardness differential in an abrasively contaminated lubricated pair may not always reduce the rate of damage to the harder surface.     

Limits of topographic measurement by the scanning tunnelling and atomic force microscopes

Parameters describing the topographic character of a surface (height, surface wavelength, slope and curvature) can be derived from equivalent sinusoidal profiles. The response of a surface-measuring instrument may be modelled in terms of instrument parameters such as stylus radius, and scanning range and resolution. The performance of the instrument may then be mapped as a zone in amplitude-wavelength (AW) space to show the sinusoidal profiles it is capable of measuring. In a first-order analysis the STM and AFM are considered as equivalent to contact-stylus instruments with a notional stylus radius equal to the tip radius plus the gap. Comparisons between different instruments and types of instrument are readily made by mapping in AW space. The error arising from convolution of the sinusoidal profile with that of the finite tip may be quantified and plotted as contours in AW space.