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SpringerBriefs in Computer Science
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SpringerBriefs in Computer Science
Wang, Hongxing; Weng, Chaoqun; Yuan, Junsong
This book presents a systematic study of visual pattern discovery, from unsupervised to semi-supervised manner approaches, and from dealing with a single feature to multiple types of features. Furthermore, it discusses the potential applications of discovering visual patterns for visual data analytics, including visual search, object and scene recognition.
It is intended as a reference book for advanced undergraduates or postgraduate students who are interested in visual data analytics, enabling them to quickly access the research world and acquire a systematic methodology rather than a few isolated techniques to analyze visual data with large variations. It is also inspiring for researchers working in computer vision and pattern recognition fields. Basic knowledge of linear algebra, computer vision and pattern recognition would be helpful to readers.Details
Published by: Springer
Publication Date: 2017-06-29
Format: Paperback
ISBN-13: 9789811048395
DOI: 10.1007/978-981-10-4840-1
Dimensions: 235cm x155cm
Pages: 87