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数字图书馆

DOI: 10.11834/jig.200108174

Keywords: 数字图书馆,研究状况,数字化技术,信息存储,信息压缩,信息检索,信息分类,信息索引

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Abstract:

这是本刊特为海内外正在就读和学成立业的博士、博士后青年学者们开辟的一片科普园地.深学浅著是一门德识、慧学、素质修养的学问.你们的新知识、新调研、新观察、新目光、新展望,能够用尽可能深入浅出、通俗流畅的语言,汇报给祖国人民、家乡父老子弟乡亲们吗?中华博士园地,乃耕耘忠孝之地,科教兴国、民族昌盛之地.要用慈母听得懂的语言,写出你们的心声!

References

[1]  [1]高文,刘峰,黄铁军等.数字图书馆.北京:清华大学出版社.
[2]  [3]www. d-library. com. cn
[3]  [5]Rui Y, Huang T S, Chang S F. Image retrieval: Past, present, and future. In:Invited paper in Iht Symposium on Multimedia Information Processing. Taipei, Taiwan,1997.
[4]  [7]Rui Y, Huang T S, Mehrotra S et al. Relevance feedback: A power tool forinteractive content-based image retrieval. IEEE trans. Circuits and systems for videotechnology. 1998,8(5): 644~655.
[5]  [9]Ishikawa Y, Subramanya R, Faloutsos C. Mindreader: Query databases through multipleexamples. In: Proceeding of the 24th VLDB Conference, New York, 1998:433~438.
[6]  [11]Flickner M, Sawhrey H, Niblack W et al. Query by image and video content: The QBICsystem. IEEE Computer, 1995, 28(9) :23~32.
[7]  [13]Smith J, Chang S F. VisualSEEK:A fully automated contentbased image query system.In:Proceedings of the Fourth ACM Multimedia Conference, Boston, 1996: 87 ~ 98.
[8]  [15]Minka T P, Picard R. Interactive learning Using a "Society of Models.”Technical report 349, MIT Media Lab, 1995.
[9]  [17]Gevers T, Smeulders A W M. The PicToSeek WWW image search system. In:IEEEInternational Conference on Multimedia Computing and Systems, Etaly, 1999: 264~269.
[10]  [19]Cox I J, Miller M L, Omohundro S M et al. Pichunter: Bayesian relevance feedbackfor image retrieval system. In:Intl. Conf. On Pattern Recognition, Vienna, Austria, August1996: 361 ~ 369.
[11]  更多...
[12]  [21]Lijuan Duan, Wen Gao, Jiyong Ma. An adaptive refining approach for content-basedimage retrieval. In: The First IEEE Pacific-Rim Conference on Multimedia. University ofSydney, Australia. December 13-15, 2000.
[13]  [16]Vasconcelos N, Lippman A. Bayesian representations and learning mechanisms forcontent based image retrieval. In:SPIE Storage and Retrieval for Media Databases 2000, SanJose, California, 2000.
[14]  [18]Wood M E J, Campbell N W, Thomas B T. Iterative refinement by relevance feedbackin content-based digital image retrieval. In: ACM Multimedia, Bristol, England, 1998.
[15]  [20]Lijuan Duan, Wen Gao, Jiyong Ma. A rich get richer strategy for content-basedimage retrieval. In: Fourth International Conference On Visual Information Systems, 2-4November, 2000, Lyon, France.
[16]  [2]www.ssreader.com
[17]  [4]www. digiark. com/tushu/index. html
[18]  [6]Gudivada V N. Content-based image retrieval systems. IEEE Computer, 1995,28(9):18~22.
[19]  [8]Rui Y, Huang T S. A novel relevance feedback technique in image retrieval. In:Proceedings of ACM Multimedia\'99, Oriando, 1999:67~70.
[20]  [10]Lee C, Ma W Y, Zhang H. Information embedding based on user\'s relevance feedbackfor image retrieval. Technical report of HP Labs, 1998.
[21]  [12]Pentland A P, Picard R, Sclaroff S. Photobook: Content-based manipulation of imagedatabases. International Journal of Computer Vision, 1996,18(3) : 233~ 254.
[22]  [14]Ogle V, Stonebraker M. Chabot: Retrieval from a relational database of images.IEEE Computer, 1995,28: 40~ 48.

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