共查询到19条相似文献，搜索用时 562 毫秒
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分析了以往经典的多核SoC任务调度算法的基本原理和性能,并以负载平衡为目的,对多核SoC的任务调度算法进行优化。该算法在流水线调度算法的基础上,引入制导的自调度（GSS）方法,应用于多核SoC的任务调度。通过实验证明该调度策略在系统资源、开销等方面均有较好分配,减少了任务延时,系统的性能有了显著提高,达到负载平衡的目的。 相似文献
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提出一种异构多核平台上的性能评估方法.该方法与多核任务的动态划分和调度算法相结合,可以获得给定任务集在不同硬件平台上的任务加速比.与此同时,针对不同层次的实时性需求,该算法可以给出硬件平台配置及任务划分方案.仿真实验和FPGA原型系统的测试数据表明,在任务之间存在依赖关系的情况下,该方法能够获得90%的精确度,在无依赖关系时,算法的精度为98.9%. 相似文献
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随着多核技术的不断发展,多核CPU已经成为处理器市场的主流。如何充分利用多核的优势提高应用程序的性能是开发人员不得不面对的课题。多核系统为开发人员提供了一个实现并行计算的重要平台。探讨了多核处理器平台上的OpenMP编译指令优化,介绍OpenMP并行编程的相关知识。 相似文献
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由于DSP芯片的强大存储容量和运算速度,成为了视频图像处理技术的基础,H.264是用于编码表示视频信息的新一代标准,具有更低的码率、更高的图像质量和更强的容错能力。通过利用DSP的超长指令字结构(VL1W)和流水线结构并综合应用其它手段设计优化程序,使H.264编码效率大大提高。系统包括视频采集模块、视频编码模块和视频输出模块。根据TMS320DM642的结构和功能特点对编码算法进行内核优化和T264代码优化以增强其有效性。 相似文献
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在简要介绍视频监控系统界面设计的基础上,提出了一种基于Qt4的远程视频监控系统设计与实现方法,并在Qt4．5．0和Red Hat Enterprise Linux4操作系统下进行了实现。实验结果表明,系统各项功能满足远程视频监控的要求。 相似文献
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利用Hadamard变换的去相关性能和3D小波视频编码的帧结构特性,提出了一种新的面向空间通信视频编码算法的业务流模型。实验结果表明,新模型产生的仿真数据能够匹配视频源数据的概率密度函数,能够模拟空间通信视频源数据的短时相关性和长时相关性,在漏桶评估实验中,模型仿真数据与视频源数据的排队性能匹配效果好,可以作为空间通信系统研究的视频源模型。 相似文献
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提出一种可有效处理多个数据集合之间变量关系的集成多核典型相关分析方法,构造一个特殊的核函数,使其更好地将原始样本数据映射到高维空间;基于支持向量机,在选择一个优化参数的基础上最大化多组数据集变量间的关系,以寻求整体相关性最大。在多特征手写体数字库上的实验证明,相比传统的典型相关分析与核典型相关分析方法,基于优化参数的集成多核典型相关分析方法具有更优的性能。 相似文献
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H.264又称做MPEG-4 Part 10,是国际标准化组织(Internotional Organization for Standardization,简称ISO)和国际电信联盟(International Telecommunication Union,简称ITU)共同提出的继MPEG4之后的视频压缩格式。同以往的视频编码标准相比,H.264编码性能提高了约33%。H.264的压缩率大概是现有的MPEG-4 ASP(MPEG-4高级简易版本)的两倍,视频图像的清晰程度也更高。在低于1Mbit/s的速率下,H.264标准能够达到DVD的成像质量,适于不同的网络视频传输。江西省政务网高清视频系统的骨干设备RADVISION MCU和SONY XG80都是H.264的应用目标,政务网高清系统是基于H.264视频编码技术的视频系统。 相似文献
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为去除网络入侵数据集中的冗余和噪声特征,降低数据处理难度和提高检测性能,提出一种基于特征选择和支持向量机的入侵检测方法。该方法采用提出的特征选择算法选取最优特征组合,并以支持向量机为分类器建立模型,应用于入侵检测系统。仿真结果表明,本文方法不仅可以减少特征维数,降低训练和测试时间,还能提高入侵检测的分类准确率。 相似文献
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《Information processing & management》2022,59(2):102868
With the continuous development of intelligent transportation systems, vehicle-related fields have emerged a research boom in detection, tracking, and retrieval. Vehicle re-identification aims to judge whether a specific vehicle appears in a video stream, which is a popular research direction. Previous researches have proven that the transformer is an efficient method in computer vision, which treats a visual image as a series of patch sequences. However, an efficient vehicle re-identification should consider the image feature and the attribute feature simultaneously. In this work, we propose a vehicle attribute transformer (VAT) for vehicle re-identification. First, we consider color and model as the most intuitive attributes of the vehicle, the vehicle color and model are relatively stable and easy to distinguish. Therefore, the color feature and the model feature are embedded in a transformer. Second, we consider that the shooting angle of each image may be different, so we encode the viewpoint of the vehicle image as another additional attribute. Besides, different attributes are supposed to have different importance. Based on this, we design a multi-attribute adaptive aggregation network, which can compare different attributes and assign different weights to the corresponding features. Finally, to optimize the proposed transformer network, we design a multi-sample dispersion triplet (MDT) loss. Not only the hardest samples based on hard mining strategy, but also some extra positive samples and negative samples are considered in this loss. The dispersion of multi-sample is utilized to dynamically adjust the loss, which can guide the network to learn more optimized division for feature space. Extensive experiments on popular vehicle re-identification datasets verify that the proposed method can achieve state-of-the-art performance. 相似文献
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The problem of content-based video retrieval continues to pose a challenge to the research community, the performance of video retrieval systems being low due to the semantic gap. In this paper we consider whether taking advantage of context can aid the video retrieval process by making the prediction of relevance easier, i.e. if it is easier for a classification system to predict the relevance of a video shot under a given context, then that context has potential in also improving retrieval, since the underlying features better differentiate relevant from non-relevant video shots. We use an operational definition of context, where datasets can be split into disjoint sub-collections which reflect a particular context. Contexts considered include task difficulty and user expertise, among others. In the classification process, four main types of features are used to represent video-shots: conventional low-level visual features representing physical properties of the video shots, behavioral features which are based on user interaction with the video shots, and two different bag-of-words features obtained from the Automatic Speech Recognition from the audio of the video. 相似文献
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《Information processing & management》2016,52(5):885-910
One of the important problems in text classification is the high dimensionality of the feature space. Feature selection methods are used to reduce the dimensionality of the feature space by selecting the most valuable features for classification. Apart from reducing the dimensionality, feature selection methods have potential to improve text classifiers’ performance both in terms of accuracy and time. Furthermore, it helps to build simpler and as a result more comprehensible models. In this study we propose new methods for feature selection from textual data, called Meaning Based Feature Selection (MBFS) which is based on the Helmholtz principle from the Gestalt theory of human perception which is used in image processing. The proposed approaches are extensively evaluated by their effect on the classification performance of two well-known classifiers on several datasets and compared with several feature selection algorithms commonly used in text mining. Our results demonstrate the value of the MBFS methods in terms of classification accuracy and execution time. 相似文献
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Within the context of Information Extraction (IE), relation extraction is oriented towards identifying a variety of relation phrases and their arguments in arbitrary sentences. In this paper, we present a clause-based framework for information extraction in textual documents. Our framework focuses on two important challenges in information extraction: 1) Open Information Extraction and (OIE), and 2) Relation Extraction (RE). In the plethora of research that focus on the use of syntactic and dependency parsing for the purposes of detecting relations, there has been increasing evidence of incoherent and uninformative extractions. The extracted relations may even be erroneous at times and fail to provide a meaningful interpretation. In our work, we use the English clause structure and clause types in an effort to generate propositions that can be deemed as extractable relations. Moreover, we propose refinements to the grammatical structure of syntactic and dependency parsing that help reduce the number of incoherent and uninformative extractions from clauses. In our experiments both in the open information extraction and relation extraction domains, we carefully evaluate our system on various benchmark datasets and compare the performance of our work against existing state-of-the-art information extraction systems. Our work shows improved performance compared to the state-of-the-art techniques. 相似文献
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《Information processing & management》1999,35(3):381-400
The VISION (video indexing for searching over networks) digital video library system has been developed in our laboratory as a testbed for evaluating automatic and comprehensive mechanisms for video archive creation and content-based search, filtering and retrieval of video over local and wide area networks. In order to provide access to video footage within seconds of broadcast, we have developed a new pipelined digital video processing architecture which is capable of digitizing, processing, indexing and compressing video in real time on an inexpensive general purpose computer. These videos were automatically partitioned into short scenes using video, audio and closed-caption information. The resulting scenes are indexed based on their captions and stored in a multimedia database. A client-server-based graphical user interface was developed to enable users to remotely search this archive and view selected video segments over networks of different bandwidths. Additionally, VISION classifies the incoming videos with respect to a taxonomy of categories and will selectively send users videos which match their individual profiles. 相似文献
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一种基于视频的无损信息隐藏方法 总被引：2，自引：0，他引：2
描述了一种基于MPEG-Ⅱ彩色视频中的无损信息隐藏方法，该方法在Alattar算法的基础上，使宿主矢量类型的判别由四个不等式，减小到两个不等式，降低了算法的时间复杂度。数据嵌入过程中采用简单数据链路SDL成帧。在局域网上进行了隐秘传输模拟实验，从嵌入信息的视频中正确提取出所嵌入汉字或二值指纹图像后，原宿主视频可无损恢复。该方法较适用于视频中的隐秘传输及产权保护等领域。 相似文献