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Syntactic pattern recognition [electronic resource] / Mariusz Flasinski.

By: Flasinski, Mariusz.
Material type: materialTypeLabelComputer fileSeries: Series in computer vision ; v. 6.Publisher: Singapore : World Scientific Publishing Co. Pte Ltd., ©2019Description: 1 online resource (404 p.) : ill.ISBN: 9789813278479.Subject(s): Pattern perception | Pattern recognition systemsGenre/Form: Electronic books.DDC classification: 006.4 Online resources: Access to full text is restricted to subscribers. Summary: "This unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed. This must-have volume provides a good read and serves as an excellent source of reference materials for researchers, academics, and postgraduate students in the fields of pattern recognition, machine perception, computer vision and artificial intelligence."-- Publisher's website.
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Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Title from web page (viewed April 2, 2019).

Includes bibliographical references and index.

"This unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed. This must-have volume provides a good read and serves as an excellent source of reference materials for researchers, academics, and postgraduate students in the fields of pattern recognition, machine perception, computer vision and artificial intelligence."-- Publisher's website.

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