Overview
- Features applications of pattern recognition techniques to real-world problems with a focus on mathematical methodologies
- Interdisciplinary research from leaders in the field
- Contributions focus on current experimental and theoretical discoveries yielding new insights ?
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 30)
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Table of contents (12 papers)
Keywords
About this book
This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of Pattern Recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies which yield new insights that provide key advances in the field.
This book will be suitable for scientists and researchers in optimization, numerical methods, computer science, statistics and for differential geometers and mathematical physicists.
Editors and Affiliations
Bibliographic Information
Book Title: Mathematical Methodologies in Pattern Recognition and Machine Learning
Book Subtitle: Contributions from the International Conference on Pattern Recognition Applications and Methods, 2012
Editors: Pedro Latorre Carmona, J. Salvador Sánchez, Ana L.N. Fred
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-1-4614-5076-4
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media New York 2013
Hardcover ISBN: 978-1-4614-5075-7Published: 10 November 2012
Softcover ISBN: 978-1-4939-0092-3Published: 13 December 2014
eBook ISBN: 978-1-4614-5076-4Published: 09 November 2012
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: VIII, 196
Topics: Systems Theory, Control, Optimization, Math Applications in Computer Science, Pattern Recognition