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Mathematical Methodologies in Pattern Recognition and Machine Learning

Contributions from the International Conference on Pattern Recognition Applications and Methods, 2012

Jezik EngleskiEngleski
Knjiga Tvrdi uvez
Knjiga Mathematical Methodologies in Pattern Recognition and Machine Learning Pedro Latorre Carmona
Libristo kod: 01428191
Nakladnici Springer-Verlag New York Inc., studeni 2012
This volume features key contributions from the International Conference on Pattern Recognition Appl... Cijeli opis
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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.

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Informacije o knjizi

Puni naziv Mathematical Methodologies in Pattern Recognition and Machine Learning
Autor Pedro Latorre Carmona, J. Salvador Sánchez, Ana L.N. Fred
Jezik Engleski
Uvez Knjiga - Tvrdi uvez
Datum izdanja 2012
Broj stranica 196
EAN 9781461450757
ISBN 1461450756
Libristo kod 01428191
Nakladnici Springer-Verlag New York Inc.
Težina 452
Dimenzije 243 x 165 x 18

Kategorija

Reference, Information & Interdisciplinary subjects > Research & information: general > Information theory > Cybernetics & systems theory
Computing & Information Technology > Computer science > Mathematical theory of computation > Maths for computer scientists
Computing & Information Technology > Computer science > Artificial intelligence > Machine learning
Computing & Information Technology > Computer science > Artificial intelligence > Pattern recognition
Mathematics & Science > Mathematics > Optimization
Mathematics & Science > Mathematics > Applied mathematics
Computing & Information Technology > Business applications > Mathematical & statistical software
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