基于深度学习的双流程短视频分类方法

随着智能手机和5G网络的普及,短视频已经成为人们碎片时间获取知识的主要途径。针对现实生活场景短视频数据集不足及分类精度较低等问题,提出融合深度学习技术的双流程短视频分类方法。在主流程中,构建A-VGG-3D网络模型,利用带有注意力机制的VGG网络提取特征,采用优化的3D卷积神经网络进行短视频分类,提升短视频在时间维度上的连续性、平衡性和鲁棒性。在辅助流程中,使用帧差法判断镜头切换抽取出短视频中的若干帧,通过滑动窗口机制与级联分类器融合的方式对其进行多尺度人脸检测,进一步提高短视频分类准确性。实验结果表明,该方法在UCF101数据集和自建的生活场景短视频数据集上对于非剧情类与非访谈类短视频的查准率和查全率最高达到98.9%和98.6%,并且相比基于C3D网络的短视频分类方法,在UCF101数据集上的分类准确率提升了9.7个百分点,具有更强的普适性。     

融合包注意力机制的监控视频异常行为检测EI北大核心CSCD

针对监控视频中行人非正常行走状态的异常现象,提出了一个端到端的异常行为检测网络,以视频包为输入,输出异常得分.时空编码器提取视频包时空特征后,利用基于隐向量的注意力机制对包级特征进行加权处理,最后用包级池化映射出视频包得分.本文整合了4个常用的异常行为检测数据集,在整合数据集上进行算法测试并与其他异常检测算法进行对比.多项客观指标结果显示,本文算法在异常事件检测方面有着显著的优势.     

一种基于TextTiling的镜头边界检测算法

镜头边界检测是基于内容的视频检索中的关键技术,提出一种利用TextTiling方法来识别视频镜头边界的算法。通过滑动窗口对视频进行初步切割,利用主成分分析将视频帧投影到特征子空间,并在投影空间上计算相邻帧间距离,再根据相邻窗口之间的深度值确定视频镜头边界。针对TREC-2001视频测试数据集的实验结果显示,该算法检测镜头边界的平均查全率和平均查准率分别为89%和96.5%。     

从手机视频到DVD大片——2011谁是最给力的视频转换王

如今手机（甚至数码相机）基本上也都有拍摄视频的功能了,网络上不少精彩的视频,就是通过手机拍摄出来的。不过手机存储量有限,我们总不可能将这些视频一直保存在手机中吧,所以,将手机视频刻录成DVD光盘,无疑是一个非常好的解决方案：既解决了手机存储的问题,又方便我们在DVD机上欣赏手机拍摄出的“大片”。但是手机视频一般是MP4格式,将手机视频转换刻录成DVD,就必须借助一些软件工具来完成,本期我们就对4款流行的视频转换刻录DVD工具进行详细评测,供大家选择参考。     

基于 YOLOv5s 融合 SENet 的车辆目标 检测技术研究

针对交通监控视频的车辆目标检测技术在早晚高峰等交通拥堵时段,车辆遮挡严重且误、漏检 率较高的问题,提出一种基于 YOLOv5s 网络的改进车辆目标检测模型。将注意力机制 SE 模块分别引入 YOLOv5s 的 Backbone 主干网络、Neck 网络层和 Head 输出端,增强车辆重要特征并抑制一般特征以强化检测 网络对车辆目标的辨识能力,并在公共数据集 UA-DETRAC 和自建数据集上训练、测试。将查准率、查全率、 均值平均精度作为评价指标,结果显示 3 项指标相比于原始网络均有明显提升,适合作为注意力机制的引入位 置。针对 YOLOv5s 网络中正、负样本与难易样本不平衡的问题,网络结合焦点损失函数 Focal loss,引入 2 个 超参数控制不平衡样本的权重。结合注意力机制 SE 模块和焦点损失函数 Focal loss 的改进检测网络整体性能提 升,均值平均精度提升了 2.2 个百分点,有效改善了车流量大时的误检、漏检指标。     

基于备选路径集的在线最短耗时公交换乘方法

面向城市公交出行者,在给定出行起讫点及起始时间的情况下,提出一种基于备选路径集的在线最短耗时公交换乘方法：在预处理阶段离线地运用双向广度优先搜索方法得到点对之间的静态备选路径集;结合实时公交到站时间预测数据或发车间隔等静态的公交运营数据,进行最短耗时评估,在线地从中选择耗时最短的路径。将该方法运用于沈阳公交路网案例中（公交到站时间预测数据仿真生成）,并嵌入沈阳市公交出行查询系统,结果表明了其实用性。     

iMakeup:特定领域的大规模长视频数据集——用于细粒度视频语义内容描述

实际生活中,大多数视频均含有若干动作或物体,简单的单句描述难以展现视频中的全部信息,而各类长视频中,教学视频步骤清晰、逻辑明确,容易从中提取特征并使用深度学习相关算法进行实验验证,从长视频中提取复杂信息成为研究人员日益关注的问题之一.为此,文中收集整理了一个命名为iMakeup的大规模的美妆类教学视频数据集,其包含总时长256 h的热门50类2 000个长视频,以及12 823个短视频片段,每个片段均根据视频的逻辑步骤顺序进行划分,并标注起止时间和自然语句描述.文中主要通过视频网站下载收集原始视频,并请志愿者对视频的详细内容进行人工标注;同时统计分析了此数据集的规模大小和文本内容,并与其他类似研究领域的若干数据集进行对比;最后,展示了在此数据集上进行视频语义内容描述的基线实验效果,验证了此数据集在视频语义内容描述任务中的可行性. iMakeup数据集在收集整理时注重内容多样性和类别完整性,包含丰富的视觉、听觉甚至统计信息.除了基本的视频语义内容描述任务之外,该数据集还可用于视频分割、物体检测、时尚智能化推荐等多个前沿领域.     

融合检测与跟踪的半自动视频目标标注

针对视频图像连续帧间的目标具有冗余性,采用手动标注方式耗时耗力的问题,提出一种融合检测和跟踪算法的视频目标半自动标注框架。利用手动标注的样本离线训练改进YOLO v3模型,并将该检测模型作为在线标注的检测器。在线标注时在初始帧手动确定目标位置和标签,在后续帧根据检测框与跟踪框的IOU（Intersection-Over-Union）值自动确定目标的位置,并利用跟踪器的响应输出判断目标消失,从而自动停止当前目标标注。采用一种基于目标显著性的关键帧提取算法选择关键帧。采用自建舰船目标数据集进行了改进YOLO v3检测性能对比实验,并采用舰船视频序列验证了提出的视频目标半自动标注方法的有效性。实验结果表明,该方法可以显著提高标注效率,能够快速生成标注数据,适用于海上舰船等场景的视频目标标注任务。     

音频情感感知与视频精彩片段提取

为了将伴生音频数据的情感语义用于引导视频精彩片段的提取,提出一种音频感知驱动下的视频精彩片段提取方法.为提取伴生音频数据的情感语义,使用一个基于分层二叉树支持向量机的音频分类器提取中层音频类型,并集成了一个情感映射模型以感知高层情感语义;然后利用该前置音频情感感知模型实现伴生音频情感语义的波动分析,并进一步以精彩片段起止定位策略和音视频同步修订为辅助手段,实现视频精彩片段的定位.文中方法以音频数据情感语义波动序列为核心枢纽,以两阶段音频情感感知模型为前导分析,构建了一个完整的音频情感驱动下视频精彩片段提取架构.实验结果表明,在保证一定查准率的情况下,音频情感驱动下的视频精彩片段提取具有较好的通用性,较高的查全率以及完整度.     

一种足球视频精彩事件检测方法

限于当前的技术水平,视频检索技术难以在底层特征与高层语义之间建立通用的视频分析模型.文中结合足球视频的领域知识,着重分析了一类特殊的语义事件--精彩事件,基于统计的方法提出了动态贝叶斯网络事件检测模型,以及相应的学习和推理算法.实验结果表明,该方法可有效地提取足球视频中的精彩语义事件,具有较高的查全率和查准率,较强的鲁棒性,是一种很有前景的视频语义事件检测方法;同时证明了,通过结合某一领域知识,底层特征与高层语义之间是可以建立起某种联系的.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.