首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   2153篇
  免费   80篇
  国内免费   109篇
电工技术   16篇
综合类   106篇
化学工业   26篇
金属工艺   12篇
机械仪表   58篇
建筑科学   23篇
矿业工程   5篇
能源动力   4篇
轻工业   6篇
水利工程   3篇
石油天然气   1篇
武器工业   6篇
无线电   363篇
一般工业技术   30篇
冶金工业   5篇
原子能技术   3篇
自动化技术   1675篇
  2023年   2篇
  2022年   3篇
  2021年   4篇
  2020年   12篇
  2019年   4篇
  2018年   3篇
  2017年   9篇
  2016年   16篇
  2015年   28篇
  2014年   76篇
  2013年   53篇
  2012年   119篇
  2011年   134篇
  2010年   102篇
  2009年   110篇
  2008年   149篇
  2007年   187篇
  2006年   142篇
  2005年   101篇
  2004年   104篇
  2003年   136篇
  2002年   127篇
  2001年   95篇
  2000年   116篇
  1999年   112篇
  1998年   123篇
  1997年   93篇
  1996年   63篇
  1995年   43篇
  1994年   45篇
  1993年   22篇
  1992年   3篇
  1991年   6篇
排序方式: 共有2342条查询结果,搜索用时 421 毫秒
81.
高等医学院校的形态学实验考试是对学生的实践能力的检测,以往传统的形态考试效率低下,浪费人力、物力和时间资源.针对这些现状及需求设计了医学形态学多媒体投影考试系统,本系统研究过程主要采用了COM(组件对象模型)软件技术,通过COM定义了文件数据组件、数据库组件的对象模型及通信接口,完成了数据的传输及安全控制;主要给出了考试系统的总体设计与功能,系统在实际应用中取得了一定的经济效益和社会效益并深化了教育改革.  相似文献   
82.
提出一种基于两跳分簇网络结构的安全合作处理密钥管理协议,能支持无线多媒体传感器网络的合作处理.通过建立簇内和邻簇的密钥对,明显降低了存储开销,解决了密钥对建立和更新过程中通信开销大的问题.性能分析和仿真结果显示,密钥对建立和簇密钥更新通信开销分别减少300%和50%,并有抵制俘获攻击的能力.与不加密直接传输进行比较,加密合作传输的网络性能更优,特别是网络生存周期提高了153%.  相似文献   
83.
多媒体查询语言及其评价准则   总被引:1,自引:0,他引:1  
随着多媒体技术和多媒体相关应用的发展,对有效检索多媒体信息的要求越来越迫切.查询语言作为信息检索的有效工具,其研究也越来越受到关注.对现有的多媒体查询语言进行了全面的综述,将它们分为两类:专用语言和通用语言.尽管查询语言对多媒体信息系统提供有效的查询服务至关重要,但目前仍没有较好的多媒体查询语言评价准则.因此,针对多媒体查询语言的查询表达能力设计准则共16条,并根据这些准则对多媒体查询语言进行了评价.评价结果表明,这些语言能满足用户的基本查询要求,但在高级语义查询和不确定查询等方面还有欠缺.最后展望了多媒体查询语言的未来研究方向.  相似文献   
84.
针对目前C语言教学中广泛存在的学时少与信息量大的矛盾。分析了传统教学手段与多媒体教学手段的利与弊,提出了以传统教学手段为主。多媒体教学手段为辅的授课方法,以提高教学质量。  相似文献   
85.
Mining of music data is one of the most important problems in multimedia data mining. In this paper, two research issues of mining music data, i.e., online mining of music query streams and change detection of music query streams, are discussed. First, we proposed an efficient online algorithm, FTP-stream (Frequent Temporal Pattern mining of streams), to mine all frequent melody structures over sliding windows of music melody sequence streams. An effective bit-sequence representation is used in the proposed algorithm to reduce the time and memory needed to slide the windows. An effective list structure is developed in the FTP-stream algorithm to overcome the performance bottleneck of 2-candidate generation. Experiments show that the proposed algorithm FTP-stream only needs a half of memory requirement of original melody sequence data, and just scans the music query stream once. After mining frequent melody structures, we developed a simple online algorithm, MQS-change (changes of Music Query Streams), to detect the changes of frequent melody structures in current user-centered music query streams. Two music melody structures (set of chord-sets and string of chord-sets) are maintained and four melody structure changes (positive burst, negative burst, increasing change and decreasing change) are monitored in a new summary data structure, MSC-list (a list of Music Structure Changes). Experiments show that the MQS-change algorithm is an effective online method to detect the changes of music melody structures over continuous music query streams.
Hua-Fu LiEmail:
  相似文献   
86.
The content–user gap is the difference between the limited range of content-relevant preferences that may be expressed using the MPEG-7 user interaction tools and the much wider range of metadata that may be represented using the MPEG-7 content tools. One approach for closing this gap is to make the user and content metadata isomorphic by using the existing MPEG-7 content tools to represent user (as well as content) metadata (Agius and Angelides 2006, 2007). Subsequently, user preferences may be specified for all content, without omission. Since there is a wealth of user preference and history metadata within the MPEG-7 user interaction tools that can usefully complement these specific content preferences, in this paper we develop a method by which all user and content metadata may be bridged.
Marios C. AngelidesEmail:
  相似文献   
87.
This paper deals with multimedia information access. We propose two new approaches for hybrid text-image information processing that can be straightforwardly generalized to the more general multimodal scenario. Both approaches fall in the trans-media pseudo-relevance feedback category. Our first method proposes using a mixture model of the aggregate components, considering them as a single relevance concept. In our second approach, we define trans-media similarities as an aggregation of monomodal similarities between the elements of the aggregate and the new multimodal object. We also introduce the monomodal similarity measures for text and images that serve as basic components for both proposed trans-media similarities. We show how one can frame a large variety of problem in order to address them with the proposed techniques: image annotation or captioning, text illustration and multimedia retrieval and clustering. Finally, we present how these methods can be integrated in two applications: a travel blog assistant system and a tool for browsing the Wikipedia taking into account the multimedia nature of its content.
Gabriela CsurkaEmail:

Dr. Julien Ah-Pine   joined the XRCE Grenoble as Research Engineer in 2007. He is part of the Textual and Visual Pattern Analysis group and his current research activities are related to multi-modal information retrieval and machine learning. He received his PhD degree in mathematics from Pierre and Marie Curie University (University of Paris 6). From 2003 to 2007, he was with Thales Communications, working on relational analysis, data and text mining methods and social choice theory. Dr. Marco Bressan   is Area Manager of the Textual and Visual Pattern Analysis area at Xerox Research Centre Europe. His main research interests are statistical learning and classification; image and video semantic scene understanding; image enhancement and aesthetics; object detection and recognition, particularly when dealing with uncontrolled environments. Prior to Xerox, several of his contributions in these fields were applied to a variety of scenarios including biometric solutions, data mining, CBIR and industrial vision. Dr. Bressan holds a BA in Applied Mathematics from the University of Buenos Aires, a M.Sc. in Computer Vision from the Computer Vision Centre in Spain and a Ph.D. in Computer Science and Artificial Intelligence from the Autonomous University of Barcelona. He is an active member of the network of Argentinean researchers abroad and one of the founders of the network of computer vision and cognitive science researchers. Stephane Clinchant   is Ph.D. Student at University Joseph Fourier (Grenoble, France) and at the Xerox Research Centre Europe, that he joined in 2005. Before joining XRCE, Stephane obtained a Master Degree in Computer Sciences in 2005 from the Ecole Nationale Superieure d’Electrotechnique, d’Informatique, d’Hydraulique et des Telecommunications (France). His current research interests mainly focus on Machine Learning for Natural Language Processing and Multimedia Information Access. Dr. Gabriela Csurka   is a research scientist in the Textual and Visual Pattern Analysis team at Xerox Research Centre Europe (XRCE). She obtained her Ph.D. degree (1996) in Computer Science from University of Nice Sophia - Antipolis. Before joining XRCE in 2002, she worked in fields such as stereo vision and projective reconstruction at INRIA (Sophia Antipolis, Rhone Alpes and IRISA) and image and video watermarking at University of Geneva and Institute Eurécom, Sophia Antipolis. Author of several publications in main journals and international conferences, she is also an active reviewer both for journals and conferences. Her current research interest concerns the exploration of new technologies for image content and aesthetic analysis, cross-modal image categorization and semantic based image segmentation. Yves Hoppenot   is in charge of the development and integration of new technologies in our European research Technology Showroom. He is a software expert for the production, office and services sectors. Yves joined the Xerox Research Centre Europe in 2001. He graduated from the Ecole National Superieure des Telecommunications, Brest in France, and received a Master of Science degree from the Tampere University of Technology in Finland. Dr. Jean-Michel Renders   joined the XRCE Grenoble as Research Engineer in 2001. His current research interests mainly focus on Machine Learning techniques applied to Statistical Natural Language Processing and Text Mining. Before joining XRCE, Jean-Michel obtained a PhD in Applied Sciences from the University of Brussels in 1993. He started his research activities in 1988, in the field of Robotics Dynamics and Control. Then, he joined the Joint Research Center of the European Communities to work on biologial metaphors (Genetic Algorithms, Neural Networks and Immune Networks) applied to process control. After spending one year as Visiting Scientist at York University (England), he spent 4 years applying Artificial Intelligence and Machine Learning Techniques in Industry (Tractebel - Suez). Then, he worked as Data Mining Senior Consultant and led projects in most major Belgian banks and utilities.   相似文献   
88.
Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience. Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.
Giuseppe TribulatoEmail:

Sebastiano Battiato   was born in Catania, Italy, in 1972. He received the degree in Computer Science (summa cum laude) in 1995 and his Ph.D in Computer Science and Applied Mathematics in 1999. From 1999 to 2003 he has lead the “Imaging” team c/o STMicroelectronics in Catania. Since 2004 he works as a Researcher at Department of Mathematics and Computer Science of the University of Catania. His research interests include image enhancement and processing, image coding and camera imaging technology. He published more than 90 papers in international journals, conference proceedings and book chapters. He is co-inventor of about 15 international patents. He is reviewer for several international journals and he has been regularly a member of numerous international conference committees. He has participated in many international and national research projects. He is an Associate Editor of the SPIE Journal of Electronic Imaging (Specialty: digital photography and image compression). He is director of ICVSS (International Computer Vision Summer School). He is a Senior Member of the IEEE. Giovanni Maria Farinella   is currently contract researcher at Dipartimento di Matematica e Informatica, University of Catania, Italy (IPLAB research group). He is also associate member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006. His research interests lie in the fields of computer vision, pattern recognition and machine learning. In 2004 he received his degree in Computer Science (egregia cum laude) from University of Catania. He was awarded a Ph.D. (Computer Vision) from the University of Catania in 2008. He has co-authored several papers in international journals and conferences proceedings. He also serves as reviewer numerous international journals and conferences. He is currently the co-director of the International Summer School on Computer Vision (ICVSS). Giovanni Giuffrida   is an assistant professor at University of Catania, Italy. He received a degree in Computer Science from the University of Pisa, Italy in 1988 (summa cum laude), a Master of Science in Computer Science from the University of Houston, Texas, in 1992, and a Ph.D. in Computer Science, from the University of California in Los Angeles (UCLA) in 2001. He has an extensive experience in both the industrial and academic world. He served as CTO and CEO in the industry and served as consultant for various organizations. His research interest is on optimizing content delivery on new media such as Internet, mobile phones, and digital tv. He published several papers on data mining and its applications. He is a member of ACM and IEEE. Catarina Sismeiro   is a senior lecturer at Imperial College Business School, Imperial College London. She received her Ph.D. in Marketing from the University of California, Los Angeles, and her Licenciatura in Management from the University of Porto, Portugal. Before joining Imperial College Catarina had been and assistant professor at Marshall School of Business, University of Southern California. Her primary research interests include studying pharmaceutical markets, modeling consumer behavior in interactive environments, and modeling spatial dependencies. Other areas of interest are decision theory, econometric methods, and the use of image and text features to predict the effectiveness of marketing communications tools. Catarina’s work has appeared in innumerous marketing and management science conferences. Her research has also been published in the Journal of Marketing Research, Management Science, Marketing Letters, Journal of Interactive Marketing, and International Journal of Research in Marketing. She received the 2003 Paul Green Award and was the finalist of the 2007 and 2008 O’Dell Awards. Catarina was also a 2007 Marketing Science Institute Young Scholar, and she received the D. Antonia Adelaide Ferreira award and the ADMES/MARKTEST award for scientific excellence. Catarina is currently on the editorial boards of the Marketing Science journal and the International Journal of Research in Marketing. Giuseppe Tribulato   was born in Messina, Italy, in 1979. He received the degree in Computer Science (summa cum laude) in 2004 and his Ph.D in Computer Science in 2008. From 2005 he has lead the research team at Neodata Group. His research interests include data mining techniques, recommendation systems and customer targeting.   相似文献   
89.
邹强  冯丹  曹炬  田磊  曾令仿 《计算机科学》2008,35(12):79-82
设计一个实用的分布式多媒体服务系统,存储子系统是其中的一个研究重点.根据多媒体系统的存储特点,从全新的视角提出一种存储子系统设计方案--基于对象的多媒体存储系统(Multimedia Object-based Storage System,MOSS),并分析了MOSS的系统架构和工作流程.与传统的多媒体存储技术相比,对象存储不仅能有效地改善系统I/O性能,还具有较好的安全性.以对象存储原型系统为基础,讨论了热点对象文件的分布和均匀分块优化策略.通过建立与系统相对应的数学模型,对数传率、I/O请求丢失率等性能指标作了定性分析.该研究工作对消除多媒体服务系统I/O瓶颈、进行存储子系统设计具有实际的指导意义.  相似文献   
90.
基于UPnP和UPnP AV的多媒体内容同步和回放   总被引:2,自引:0,他引:2  
张莉 《计算机科学》2008,35(5):92-94
简要描述了基于UPnP技术架构和UPnP AV规范的家庭娱乐系统(HES)的实现方案,在HES中提出了设备选择算法、轻量级可切换播放服务和快速同步算法.设备选择算法实现了用户零干预条件下的自动切换,轻量级可切换播放服务提供了一个简单高效的服务实现,而快速同步算法将媒体播放切换动作前的同步时间降低到秒数量级,与传统内容同步方法分钟级的延时相比具有重要的使用价值.  相似文献   
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号