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Machine learning and data mining in pattern recognition

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  • 215 pages
  • 8 hours of reading

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The field of machine learning and data mining, particularly in pattern recognition, is gaining popularity among researchers. Successful automatic pattern recognition systems are crucial for adapting to changing environments and new objects, necessitating robust learning capabilities. The appeal of learning in this domain stems from the unique data and the various processing stages within a pattern recognition system, leading to a distinct branch of machine learning. The workshop showcased machine learning techniques for image pre-processing, segmentation, recognition, and interpretation, with applications in document and medical image analysis. Numerous databases containing multimedia sources, such as images and text documents, have been developed, requiring effective content-based retrieval strategies. To enhance database quality, mining techniques must be employed to uncover underlying information, taking into account the specific characteristics of image sources. The exploration of mining multimedia databases is in its infancy, and the workshop aims to engage more researchers in this emerging area.

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Machine learning and data mining in pattern recognition, Petra Perner

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1999
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