基于共轭梯度法的CNN图像分类模型研究

本文针对处理图像分类的卷积神经网络(CNN)模型,设计并应用修正的三项PRP共轭梯度法(M-PRPCG)训练模型以提高图像分类的准确率。首先,基于CIFAR-10图像分类数据集构建ResNet18和VGG16卷积神经网络(CNN)模型;然后在训练集上,采用修正的三项PRP共轭梯度法(M-PRPCG)训练模型;最后在测试集上进行验证。实验结果表明,修正的三项PRP共轭梯度法(M-PRPCG)训练的ResNet18和VGG16模型相比于Adam算法训练的模型在图像分类准确率上分别提高了3.46%和1.97%。     

基于全卷积神经网络的SAR图像目标分类

近年来,卷积神经网络(Convolutional Neural Network,CNN)在合成孔径雷达(Synthetic Aperture Radar,SAR)图像目标分类中取得了较好的分类结果。CNN结构中,前面若干层由交替的卷积层、池化层堆叠而成,后面若干层为全连接层。全卷积神经网络（All Convolutional Neural Network, A-CNN）是对CNN结构的一种改进,其中池化层和全连接层都用卷积层代替,该结构已在计算机视觉领域被应用。针对公布的MSTAR数据集,提出了基于A-CNN的SAR图像目标分类方法,并与基于CNN的SAR图像分类方法进行对比。实验结果表明,基于A-CNN的SAR图像目标分类正确率要高于基于CNN的分类正确率。     

一种基于卷积神经网络的环境声音分类方法

卷积神经网络(CNN)辨别频域-时域模式的能力使其适合于环境声音分类。然而数据的相对稀缺使该方法的应用受限。所以使用数据增强与卷积神经网络结合的方法来克服这一难点。首先,提出使用音频数据增强来增加训练数据,然后提出了一种卷积神经网络模型进行分类。所提出的方法对于环境声音分类的准确率达到了79.5%,这种方法既优于没有增强的CNN模型也优于具有增强的SVM模型。     

基于迁移学习的遥感图像场景分类

在遥感图像场景分类中,基于卷积神经网络 (convolutional neural network,CNN) 的分 类算法存在对训练数据的依赖性,且在缺乏训练数据时分 类效果差等问题,提出一种基于迁移学习的分类算法。首先,选取现有的多个CNN预训练模型,利用迁 移学习的优势对模型进行微调,目的是提取图像不同的高层特征;然后,融合图像的多种高 层特征,使得特征信 息更加丰富;最后,将融合后的高层特征输入到基于逻辑回归的遥感图像分类器中,得到遥 感影像的分类结果。 在UCMerced_LandUse遥感数据集中进行实验,与现有算法进行比较分析,所提算法在3种评 价指标上有明显提 升。通过分析实验结果表明,该算法在仅有10%的训练数据下,能够 达到92.01%的分类准确率和91.61%的Kappa系数。     

基于改进CNN的增强现实变压器图像识别技术

研究了增强现实变压器图像识别技术,为解决增强现实中变压器图像识别问题,首先在介绍深度学习的经典模型之一,即卷积神经网络CNN的基础上,提出基于两个并行结构的改进卷积神经网络模型(改进CNN),利用改进CNN模型对增强现实摄像头扫描得到的图像进行分类,实现变压器图形化识别。与普通卷积神经网络、SIFT图像识别算法等对比,改进CNN具有更低的错误率,并对变压器图像识别的准确率更高,通过仿真实验验证了此方法的准确性。     

基于CNN的金属疲劳裂纹超声红外热像检测与识别方法研究

传统超声红外热像检测与识别金属疲劳裂纹主要是通过图像处理算法提取红外热图像的相关热特征,并与裂纹特征进行匹配,其过程过于繁琐,识别率较低且需要人工筛选有效特征。结合主动红外热成像技术以及卷积神经网络（Convolutional Neural Network,CNN）在金属结构无损检测与缺陷自动识别中的优势,提出了一种基于CNN的金属疲劳裂纹超声红外热像检测与识别方法。通过超声红外热成像装置对实验对象（文中为金属平板试件）进行检测,获取红外热图像并制作图像数据集。运用设计的卷积神经网络对不同尺寸裂纹的超声红外热图像进行特征提取与识别分类。此外,对所提出的方法与两种常见图像分类网络模型以及支持向量机的分类结果进行对比。实验结果表明,设计的卷积神经网络在该数据集上识别分类准确率为100%,优于其他网络模型和支持向量机的识别分类,可以有效检测与识别金属疲劳裂纹。     

基于卷积神经网络的图像分类算法综述

随着大数据的到来以及计算能力的提高,深度学习(Deep Learning, DL)席卷全球。传统的图像分类方法难以处理庞大的图像数据以及无法满足人们对图像分类精度和速度上的要求,基于卷积神经网络(Convolutional Neural Network, CNN)的图像分类方法冲破了传统图像分类方法的瓶颈,成为目前图像分类的主流算法,如何有效利用卷积神经网络来进行图像分类成为国内外计算机视觉领域研究的热点。本文在对卷积神经网络进行系统的研究并且深入研究卷积神经网络在图像处理中的应用后,给出了基于卷积神经网络的图像分类所采用的主流结构模型、优缺点、时间/空间复杂度、模型训练过程中可能遇到的问题和相应的解决方案,与此同时也对基于深度学习的图像分类拓展模型的生成式对抗网络和胶囊网络进行介绍;然后通过仿真实验验证了在图像分类精度上,基于卷积神经网络的图像分类方法优于传统图像分类方法,同时综合比较了目前较为流行的卷积神经网络模型之间的性能差异并进一步验证了各种模型的优缺点;最后对于过拟合问题、数据集构建方法、生成式对抗网络及胶囊网络性能进行相关实验及分析。      

基于CTCNet对球结膜进行糖尿病视网膜病变分类

糖尿病视网膜病变(diabetic retinopathy, DR)是一种糖尿病性微血管病变,会在球结膜微血管上有所体现,球结膜血管图像的获取比眼底图像更加便捷,但微血管的特征变化微小且难以量化。为了能够对患者进行早期辅助诊断,本文依据球结膜微血管形态与DR的关联,首先对球结膜图像进行预处理,使用限制对比度自适应直方图均衡(contrast limited adaptive histogram equalization, CLAHE)算法进行图像增强,随机处理使数据增强,然后结合卷积神经网络(convolutional neural network, CNN)和Transformer各自的网络优势构建CTCNet,对处理后的球结膜血管图像进行DR分类,分类准确率达到了97.44%,敏感度97.69%,特异性97.11%,精确度97.69%,通过实验对比CNN和Transformer, CTCNet网络性能优于其他模型,能够有效识别DR。     

基于深度卷积神经网络的图上半监督极化SAR图像分类算法

为实现在只有少量标记数据情况下的高质量的图像分类,本文提出了一种基于深度卷积神经网络的图上半监督极化SAR图像分类算法.该算法将极化SAR图像建模为无向图,并基于该无向图,定义了包含半监督项,卷积神经网络项和类标光滑项的能量函数.算法所采用的卷积神经网络提取抽象的数据驱动的极化特征.半监督项约束了有标记像素的类标在分类过程中保持不变.类标光滑项约束了像素间类标的光滑性.基于对PauliRGB图像进行超像素分割而产生的初始化类标图,交替迭代优化所定义的能量函数直至其收敛.在两幅真实极化SAR图像上的实验结果表明,该算法达到了优异的分类效果,其性能优于当前已有算法.     

基于双通道ＣＮＮ的ＦＭＣＷ雷达手势识别方法

为了提高对手势动作的分类能力,该文提出一种基于双通道卷积神经网络(CNN)的调频连续波（FMCW）雷达手势识别方法。首先利用具有一个发射天线两个接收天线的FMCW雷达对不同手势动作进行探测并收集到回波数据,之后对每个接收通道的回波数据进行预处理分别得到距离时间图、距离多普勒图与微多普勒时频谱图,然后将每个动作对应的三种彩色RGB图像进行堆叠。最后将堆叠后的彩色RGB图像输入到双通道CNN中进行手势特征提取和特征融合。实测数据处理结果表明所提基于双通道CNN手势识别方法对设计的八种手势动作的分类平均正确率为97.52%,与传统的单通道CNN相比有效地提高了对手势动作的分类能力。     

Resolution Enhancement Technology:Integrated Process Solutions using OPC

DUV lithography, using the 248 nm wavelength, is a viable manufacturing option for devices with features at 130 nm and less. Given the low kl value of the lithography, integrated process development is a necessary method for achieving acceptable process latitude. The application of assist features for rule based OPC requires the simultaneous optimization of the mask, illumination optics and the resist.Described in this paper are the details involved in optimizing each of these aspects for line and space imaging.A reference pitch is first chosen to determine how the optics will be set. The ideal sigma setting is determined by a simple geometrically derived expression. The inner and outer machine settings are determined, in turn,with the simulation of a figure of merit. The maximum value of the response surface of this FOM occurs at the optimal sigma settings. Experimental confirmation of this is shown in the paper.Assist features are used to modify the aerial image of the more isolated images on the mask. The effect that the diffraction of the scattering bars (SBs) has on the image intensity distribution is explained. Rules for determining the size and placement of SBs are also given.Resist is optimized for use with off-axis illumination and assist features. A general explanation of the material' s effect is discussed along with the affect on the through-pitch bias. The paper culminates with the showing of the lithographic results from the fully optimized system.     

Cost-effective test solutions for smart card and other integrated flash applications

From its emergence in the late 1980s as a lower cost alternative to early EEPROM technologies, flash memory has evolved to higher densities and speedsand rapidly growing acceptance in mobile applications.In the process, flash memory devices have placed increased test requirements on manufacturers. Today, as flash device test grows in importance in China, manufacturers face growing pressure for reduced cost-oftest, increased throughput and greater return on investment for test equipment. At the same time, the move to integrated flash packages for contactless smart card applications adds a significant further challenge to manufacturers seeking rapid, low-cost test.     

Theoretical analysis of the relationship between the Brillouin gain coefficient and the strain in the optical-fiber sensors

The relation between the power of the Brillouin signal and the strain is one of the bases of the distributed fiber sensors of temperature and strain. The coefficient of the Bfillouin gain can be changed by the temperature and the strain that will affect the power of the Brillouin scattering. The relation between the change of the Brillouin gain coefficient and the strain is thought to be linear by many researchers. However, it is not always linear based on the theoretical analysis and numerical simulation. Therefore, errors will be caused if the relation between the change of the Brillouin gain coefficient and the strain is regarded as to be linear approximately for measuring the temperature and the strain. For this reason, the influence of the parameters on the Brillouin gain coefficient is proposed through theoretical analysis and numerical simulation.     

An improved parallel thinning algorithm with two subiterations

The parallel thinning algorithm with two subiterations is improved in this paper. By analyzing the notions of connected components and passes, a conclusion is drawn that the number of passes and the number of eight-connected components are equal. Then the expression of the number of eight-connected components is obtained which replaces the old one in the algorithm. And a reserving condition is proposed by experiments, which alleviates the excess deletion where a diagonal line and a beeline intersect. The experimental results demonstrate that the thinned curve is almost located in the middle of the original curve connectivelv with single pixel width and the processing speed is high.     

Novel fiber-optical interferometer with miniaturized probe for in-hole measurements

Today, micro-system technology and the development of new MEMS （Micro-Electro-Mechanical Systems） are emerging rapidly. In order for this development to become a success in the long run, measurement systems have to ensure product quality. Most often, MEMS have to be tested by means of functionality or destructive tests. One reason for this is that there are no suitable systems or sensing probes available which can be used for the measurement of quasi inaccessible features like small holes or cavities. We present a measurement system that could be used for these kinds of measurements. The system combines a fiber optical, miniaturized sensing probe with low-coherence interferometry, so that absolute distance measurements with nanometer accuracy are possible.     

Study of waveguide coupling efficiency in hybrid silicon lasers

This paper presents a new method to increase the waveguide coupling efficiency in hybrid silicon lasers. We find that the propagation constant of the InGaAsP emitting layer can be equal to that of the Si resonant layer through improving the design size of the InP waveguide. The coupling power achieves 42% of the total power in the hybrid lasers when the thickness of the bonding layer is 100 nm. Our result is very close to 50% of the total power reported by Intel when the thickness of the thin bonding layer is less than 5 nm. Therefore, our invariable coupling power technique is simpler than Intel＇s.     

A rigorous proof of MIMO channel capacity’s increase with antenna number

It is well known that adding more antennas at the transmitter or at the receiver may offer larger channel capacity in the multiple-input multiple-output（MIMO） communication systems. In this letter, a simple proof is presented for the fact that the channel capacity increases with an increase in the number of receiving antennas. The proof is based on the famous capacity formula of Foschini and Gans with matrix theory.     

Teleportation of an arbitrary unknown N-qubit entangled state under the controlling of M controllers

A new quantum protocol to teleport an arbitrary unknown N-qubit entangled state from a sender to a fixed receiver under M controllers(M < N) is proposed. The quantum resources required are M non-maximally entangled Greenberger-Home-Zeilinger (GHZ) state and N-M non-maximally entangled Einstein-Podolsky-Rosen (EPR) pairs. The sender performs N generalized Bell-state measurements on the 2N particles. Controllers take M single-particle measurement along x-axis, and the receiver needs to introduce one auxiliary two-level particle to extract quantum information probabilistically with the fidelity unit if controllers cooperate with it.     

Diode-end-pumped Nd:YVO4/LBO lasers with 4.2W continuous-wave output at 457 nm

A continuous-wave (CW) 457 nm blue laser operating at the power of 4.2 W is demonstrated by using a fiber coupled laser diode module pumped Nd: YVO4 and using LBO as the intra-cavity SHG crystal With the optimization of laser cavity and crystal parameters, the laser operates at a very high efficiency. When the pumping power is about 31 W, the output at 457nm reaches 4.2 W, and the optical to optical conversion efficiency is about 13.5% accordingly. The stability of the out putpower is better than 1.2% for 8 h continuously working.     

Call for Papers

正Wireless Body-area Networks The last decade has witnessed the convergence of three giant worlds:electronics,computer science and telecommunications.The next decade should follow this convergence in most of our activities with the generalization of sensor networks.In particular with the progress in medicine,people live longer and the aging of population will push the development of wireless personal networks