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Titlebook: Computer Analysis of Images and Patterns; 9th International Co W?adys?aw Skarbek Conference proceedings 2001 Springer-Verlag Berlin Heidelb

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書(shū)目名稱(chēng)Computer Analysis of Images and Patterns
副標(biāo)題9th International Co
編輯W?adys?aw Skarbek
視頻videohttp://file.papertrans.cn/234/233438/233438.mp4
概述Includes supplementary material:
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Computer Analysis of Images and Patterns; 9th International Co W?adys?aw Skarbek Conference proceedings 2001 Springer-Verlag Berlin Heidelb
描述Computer analysis of images and patterns is a scienti c eld of longstanding tradition, with roots in the early years of the computer era when electronic brains inspired scientists. Moreover, the design of vision machines is a part of humanity’s dream of the arti cial person. I remember the 2nd CAIP, held in Wismar in 1987. Lectures were read in German, English and Russian, and proceedings were also only partially written in English. The conference took place under a di erent political system and proved that ideas are independent of political walls. A few years later the Berlin Wall collapsed, and Professors Sommer and Klette proposed a new formula for the CAIP: let it be held in Central and Eastern Europe every second year. There was a sense of solidarity with scienti c communities in those countries that found themselves in a state of transition to a new economy. A well-implemented idea resulted in a chain of successful events in Dresden (1991), Budapest (1993), Prague (1995), Kiel (1997), and Ljubljana (1999). This year the conference was welcomed at Warsaw. There are three invited lectures and about 90 contributions written by more than 200 authors from 27 countries. Besides Pol
出版日期Conference proceedings 2001
關(guān)鍵詞Augmented Reality; Document Analysis; Feature Extraction; Image Reconstruction; Image Sequences; Medical
版次1
doihttps://doi.org/10.1007/3-540-44692-3
isbn_softcover978-3-540-42513-7
isbn_ebook978-3-540-44692-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2001
The information of publication is updating

書(shū)目名稱(chēng)Computer Analysis of Images and Patterns影響因子(影響力)




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns被引頻次




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns年度引用




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns年度引用學(xué)科排名




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns讀者反饋




書(shū)目名稱(chēng)Computer Analysis of Images and Patterns讀者反饋學(xué)科排名




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An Overview of MPEG-7 Motion Descriptors and Their Applicationss cover a wide range of functionality and hence enable several applications. We present the salient parts of the syntax, the semantics and the associated extraction of each of these descriptors. We discuss the possible applications for these descriptors and associated complexity trade-offs. We then
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Image Retrieval Using Spatial Color Informationbblock approach with a large number of blocks and minimal color information for each block. Binary Thresholded Histogram and Extended Binary Thresholded Histogram are defined. Only 40 numbers are used to describe an image. Computing the distance is done by a very fast bitewise sum mod 2 operation.
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Coding of Irregular Image Regions by SA DFTeriodic data extension rather than data shifts, hence, in contrast to SA DCT segment reconstruction is possible even if part of contour data is missing. Visually the quality of images reconstructed from the part of SA DFT samples is almost as good as for the SA DCT, especially for high compression r
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Fast PNN Using Partial Distortion Searche consider the utilization of the partial distortion search technique in order to reduce the workload caused by the distance calculations in the PNN. By experiments, we show that the simple improvement reduces the run time down to 50–60%
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