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Titlebook: Machine Learning and Data Mining in Pattern Recognition; First International Petra Perner,Maria Petrou Conference proceedings 1999 Springe

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发表于 2025-3-21 16:53:06 | 显示全部楼层 |阅读模式
书目名称Machine Learning and Data Mining in Pattern Recognition
副标题First International
编辑Petra Perner,Maria Petrou
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Machine Learning and Data Mining in Pattern Recognition; First International  Petra Perner,Maria Petrou Conference proceedings 1999 Springe
描述The field of machine learning and data mining in connection with pattern recognition enjoys growing popularity and attracts many researchers. Automatic pattern recognition systems have proven successful in many applications. The wide use of these systems depends on their ability to adapt to changing environmental conditions and to deal with new objects. This requires learning capabilities on the parts of these systems. The exceptional attraction of learning in pattern recognition lies in the specific data themselves and the different stages at which they get processed in a pattern recognition system. This results a specific branch within the field of machine learning. At the workshop, were presented machine learning approaches for image pre-processing, image segmentation, recognition and interpretation. Machine learning systems were shown on applications such as document analysis and medical image analysis. Many databases are developed that contain multimedia sources such as images, measurement protocols, and text documents. Such systems should be able to retrieve these sources by content. That requires specific retrieval and indexing strategies for images and signals. Higher quali
出版日期Conference proceedings 1999
关键词Data Mining; Image Processing; Intelligent Data Analysis; Pattern Recognition; classification; learning; m
版次1
doihttps://doi.org/10.1007/3-540-48097-8
isbn_softcover978-3-540-66599-1
isbn_ebook978-3-540-48097-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1999
The information of publication is updating

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Conference proceedings 1999c pattern recognition systems have proven successful in many applications. The wide use of these systems depends on their ability to adapt to changing environmental conditions and to deal with new objects. This requires learning capabilities on the parts of these systems. The exceptional attraction
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