基于卷积神经网络和混合注意力机制的书标检测算法

为实现图书馆中机器人智能排架,提出一种基于卷积神经网络和混合注意力机制的书标检测模型。将DenseNet121引入YOLOv4以提高特征和梯度之间的传递效率,利用SPDC模块实现局部和全局特征融合,进而通过通道和空间混合注意力提高模型的特征表征能力。实验结果表明,模型的平均准确率、整体性能、参数量和模型大小均优于对比方法,且易于部署到嵌入式设备中实现在线检测,从而提高图书乱架治理的智能化水平。     

G-YOLO:基于改进YOLOv5的嵌入式小目标缺陷检测算法

针对人工检测缺陷模式或YOLOv5等深度学习算法对工业产品的缺陷检测存在识别准确率低、模型参数规模大等问题,提出一种对微小缺陷端到端检测的嵌入式算法G-YOLO.该算法使用卷积核为3和卷积核为1的双层卷积FConv模块,改善了原单层卷积带来的参数量较大的问题;改进的轻量级跨阶段GSP模块融合坐标注意力机制用于主干网络中能够利用冗余信息实现廉价的线性操作和聚焦缺陷信息来增强特征,以提高网络对缺陷特征的提取能力;去除原YOLOv5的颈部模块,减少网络的参数量和提升网络检测速度.结果表明,G-YOLO嵌入式算法减少了模型大小,改善了缺陷检测的效果,较好地满足轻量化嵌入式模型的要求.     

嵌入特征预提取和注意力机制的SAR图像目标检测

合成孔径雷达(Synthetic Aperture Radar,SAR)目标识别技术广泛应用于道路、船舶等检测任务中,但合成孔径雷达图像易受散斑噪声干扰,直接将卷积神经网络(Convolutional Neural Network,CNN)应用在SAR数据集上难以高效准确地提取有效特征.针对以上问题,提出了一种嵌入特征预提取和注意力机制的SAR图像目标识别算法(Convolutional Automatic Encoder-Convolutional Neural Network-Channel and Spatial Atten-tion Mechanism,CAE-CNN-CSAM),即利用优化的Lee滤波算法降低SAR图像斑点噪声,通过编解码技术对SAR图像进行特征预提取,而后在卷积神经网络中引入注意力机制,提高算法对通道和空间特征的表达能力.在公开的Statoil/C-CORE数据集上,该算法对目标的识别准确率达到了94％,相比于目标识别准确率约为88％的CNN等基准模型具有更高的目标识别性能.     

面向边缘计算的轻量化外力破坏目标检测算法

针对在复杂边缘计算场景下外力破坏目标检测识别精度低与实时性差的问题,提出YOLO-ERFA轻量化目标检测算法。该算法采用跨阶段残差结构的CSPDarkNet53-Tiny作为特征提取网络,在保证模型轻量化的同时提高检测准确率;在此基础上,通过改进空间金字塔池化并融合高效通道注意力机制构建特征增强层以提升模型精度和对多尺度目标的检测能力,并在训练阶段使用改进的Mosaic算法增加样本背景虚化以提高模型在复杂场景下的抗干扰能力。实验结果表明,该方法在测试集上检测平均准确率达到了91.58%,在Jetson TX2平台推理速度达30 FPS,且模型内存大小仅为26.50 MB,提高了算法在边缘计算设备上部署的可行性。     

基于DenseNet的人脸图像情绪识别研究

针对人脸情绪识别类内差异大,类间差异小的特点,结合学生人脸图像的线上课堂情绪识别的场景,提出多尺度空洞卷积模块提取不同空间尺度特征的稠密深度神经网络模型,实现自然场景下学生人脸图像识别.该模型主要由多尺度空洞卷积和DenseNet神经网络两个子网络组成,其中多尺度空洞卷积由不同空洞率的四分支网络提取不同尺度特征,空洞卷积减小特征图尺寸,减少DenseNet内存资源占用;最后在DenseNet网络中结合Adam优化器和中心损失函数.使用稠密网络的旁路连接,加强情绪特征传递和复用.研究结果表明：基于稠密深度神经网络的情绪识别网络模型能够有效提高情绪分类的准确率,模型对预处理后的FER2013+数据集识别准确率达到93.99%,可为线上教学反馈提供技术支持.     

基于卷积神经网络的灾难场景图像分类

为了对灾难场景图像进行快速分析和识别,提出了一种基于多分辨率卷积神经网络和残差注意力机制(attention module)相结合的图像分类模型.首先,对灾难场景数据集进行预处理,在相同类型的条件下将其随机划分为训练集和测试集.基于改进的卷积神经网络(convolutional neural network,CNN),提取训练集的图像特征.使用训练集图片的特征进行训练,并且在测试集图片上实现分类测试.选取DenseNet、Xception和MobileNetV2三种模型,以灾难场景数据集(Disaster_Data_Scenes)为数据集进行实验验证.结果表明:改进的Xception和MobileNetV2网络在灾难场景数据集上进行的图像分类实验测试,比原网络精度分别提升了4.56％和3.04％.其中改进的DenseNet网络比原网络模型精度分别提升9.13％、17.88％和10.27％.可见改进的卷积神经网络模型的分类精度得到有效提高.     

面向番茄病害识别的改进型SqueezeNet轻量级模型

针对番茄病害识别中深度神经网络参数过多、识别精度较低的问题,从网络轻量化和提取特征精准化的角度出发,对SqueezeNet结构进行改进.为精简fire模块,对其中Expand层的卷积核大小、网络层数以及通道数进行调整.同时,将模型与ECA模块结合,利用局部跨通道交互的方式获得各通道的注意力值,强化网络对关键特征的学习能...     

一种新的基于注意力机制的细粒度视频分析神经网络结构

针对包含细微差异动作的视频数据集,提出了一种用于分辨细粒度差异动作的深度神经网络.该网络结构由一个三维卷积(C3D)网络的轻量化变体和一个基于注意力机制的长短时记忆网络组成,优化了三维卷积网络的深度和注意力机制的权重惩罚项.实验结果表明:该网络可以有效地关注视频中的重要信息,在平均准确率和检测准确率上均有所提升.     

一种新的基于注意力机制的细粒度视频分析神经网络结构（英文）

针对包含细微差异动作的视频数据集,提出了一种用于分辨细粒度差异动作的深度神经网络.该网络结构由一个三维卷积(C3D)网络的轻量化变体和一个基于注意力机制的长短时记忆网络组成,优化了三维卷积网络的深度和注意力机制的权重惩罚项.实验结果表明:该网络可以有效地关注视频中的重要信息,在平均准确率和检测准确率上均有所提升.     

基于Ghost卷积和通道注意力机制级联结构的车辆检测方法研究

为了降低YOLOv3算法的计算量和模型体积，提高对小目标的检测能力，本文提出一种基于Ghost卷积和通道注意力机制级联结构，将其作为YOLOv3算法的特征提取网络，以减少网络计算量；在小目标预测支路引入S-RFB模块，扩大模型的感受野，更好地利用上下文信息，以提高对小目标的检测能力；使用CIOU损失作为边界框位置损失项，以加速模型的收敛．利用高斯噪声对训练样本进行数据增强，提高模型的鲁棒性．在UA-DETRAC数据集上进行实验，实验结果表明，相比于YOLOv3算法，基于Ghost卷积和通道注意力机制级联结构的G-YOLO算法的平均精度提高了2.7%，模型体积减小了67%，在复杂道路交通环境中具有良好的检测效果．     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

Features of Women's language

Language is a means of verbal communication. People use language to communicate with each other. In the society, no two speakers are exactly alike in the way of speaking. Some differences are due to age, gender, statue and personality. Above all, gender is one of the obvious reasons. The writer of this paper tries to describe the features of women＇s language from these perspectives： pronunciation, intonation, diction, subjects, grammar and discourse. From the discussion of the features of women＇s language, more attention should be paid to language use in social context. What＇s more, the linguistic phenomena in a speaking community can be understood more thoroughly.     

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.     

Achieving Unusual States of Matter Under High Pressure

正The periodicity of the elements and the non-reactivity of the inner-shell electrons are two related principles of chemistry,rooted in the atomic shell structure.Within compounds,Group I elements,for example,invariably assume the+1 oxidation state,and their chemical properties differ completely from those of the p-block elements.These general rules govern our understanding of chemical structures and reactions.Using first principles calcula-     

Exchange-Correlation and Electronic Excitation Energies from Pairing Matrix Fluctuations

We have developed an adiabatic connection to formulate the ground-state exchange-correlation energy in terms of pairing matrix linear fluctuations.This formulation of the exchange-correlation energy opens a new channel for density functional approximations based on the many-body perturbation theory.We illustrate the potential of such approaches with an approximation based on the particle-particle Random Phase Approximation(pp-RPA).This re-     

Density Functional Theory for the Response of Periodic Systems to Electric Fields Based on the Vector Potential Approach

正The electronic and nuclear(structural/vibrational)response of 1D-3D nanoscale systems to electric fields gives rise to a host of optical,mechanical,spectral,etc.properties that are of high theoretical and applied interest.Due to the computational difficulty of treating such large systems it is convenient to model them as infinite and periodic(at least,in first approximation).The fundamental theoretical/computational problem in doing so is that     

On the Thermodynamic Limit for Responses to Static Electromagnetic Fields

For molecular systems,the quantum-mechanical treatment of their responses to static electromagnetic fields usually employs a scalar-potential treatment of the electric field and a vector-potential treatment of the magnetic field.Although the potential for each field separately is associated with the choice of an(unphysical)origin,the precise choice of the origin for the electrostatic field has little consequences for the results.This is different for the     

An affordable accurate evaluation of the binding conformations predicted by molecular docking studies in bio-system

Franck-Condon factors bridge the gap between theoretical modeling and experimental observations for molecular electronic spectroscopy and electron transfer.Under the displaced harmonic oscillator approximation,multidimensional Franck-Condon factors are decomposed into a product of many one-dimensional(1D)Franck-Condon(FC)factors,and each 1D-FC factor is associated with one Huang-Rhys factor that determines the leading contribution of     

Call for Papers

<正>"The Journal of Shanghai Normal University:Mathematics"is published by Shanghai Normal University as regular issues of The Journal of Shanghai Normal University each year from 2014 in English.The editors-in-chief of the issues are professors Yuhao Cong and Maoan Han.The Journal of Shanghai Normal University was started in 1958 with