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Titlebook: Advances in Pattern Recognition; Joint IAPR Internati Francesc J. Ferri,José M. Iñesta,Pavel Pudil Conference proceedings 2000 Springer-Ver

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期刊全称Advances in Pattern Recognition
期刊简称Joint IAPR Internati
影响因子2023Francesc J. Ferri,José M. Iñesta,Pavel Pudil
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发行地址Includes supplementary material:
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Advances in Pattern Recognition; Joint IAPR Internati Francesc J. Ferri,José M. Iñesta,Pavel Pudil Conference proceedings 2000 Springer-Ver
影响因子This book constitutes the joint refereed proceedings of the 8th International Workshop on Structural and Syntactic Pattern Recognition and the 3rd International Workshop on Statistical Techniques in Pattern Recognition, SSPR 2000 and SPR 2000, held in Alicante, Spain in August/September 2000. The 52 revised full papers presented together with five invited papers and 35 posters were carefully reviewed and selected from a total of 130 submissions. The book offers topical sections on hybrid and combined methods, document image analysis, grammar and language methods, structural matching, graph-based methods, shape analysis, clustering and density estimation, object recognition, general methodology, and feature extraction and selection.
Pindex Conference proceedings 2000
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书目名称Advances in Pattern Recognition影响因子(影响力)




书目名称Advances in Pattern Recognition影响因子(影响力)学科排名




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书目名称Advances in Pattern Recognition网络公开度学科排名




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书目名称Advances in Pattern Recognition被引频次学科排名




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书目名称Advances in Pattern Recognition年度引用学科排名




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书目名称Advances in Pattern Recognition读者反馈学科排名




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Some Notes on Twenty One 21 Nearest Prototype Classifiersnd particular styles were appropriate to particular genres. The genres were generally those used by Greek and Roman writers. Elevated genres, epic and tragedy, demanded to be written in a high style; lesser genres, pastoral and satire for example, should be dressed out in a middle or low style (Sidn
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https://doi.org/10.1007/978-94-024-1020-4tead of using the multivariate models and statistical methods directly to design the classifier, we use them in order to whiten the data and then to train the perceptron. A special attention is paid to magnitudes of the weights and to optimization of the training procedure. We study an influence of
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