Pattern Recognition Theory and Applications

Pierre A. Devijver (u. a.)

ISBN 10: 3642830714 / ISBN 13: 9783642830716

Editore: Springer, 2012

Pattern Recognition Theory and Applications | Pierre A. Devijver (u. a.) | Taschenbuch | xi | Englisch | 2012 | Springer | EAN 9783642830716 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 106331298

Riassunto:

This book is the outcome of a NATO Advanced Study Institute on Pattern Recog­ nition Theory and Applications held in Spa-Balmoral, Belgium, in June 1986. This Institute was the third of a series which started in 1975 in Bandol, France, at the initia­ tive of Professors K. S. Fu and A. Whinston, and continued in 1981 in Oxford, UK, with Professors K. S. Fu, J. Kittler and L. -F. Pau as directors. As early as in 1981, plans were made to pursue the series in about 1986 and possibly in Belgium, with Professor K. S. Fu and the present editors as directors. Unfortunately, Ie sort en decida autrement: Professor Fu passed away in the spring of 1985. His sudden death was an irreparable loss to the scientific community and to all those who knew him as an inspiring colleague, a teacher or a dear friend. Soon after, Josef Kittler and I decided to pay a small tribute to his memory by helping some of his plans to materialize. With the support of the NATO Scientific Affairs Division, the Institute became a reality. It was therefore but natural that the proceedings of the Institute be dedicated to him. The book contains most of the papers that were presented at the Institute. Papers are grouped along major themes which hopefully represent the major areas of contem­ porary research. These are: 1. Statistical methods and clustering techniques 2. Probabilistic relaxation techniques 3. From Markovian to connectionist models 4.

Contenuti: Statistical Methods and Clustering Techniques.- 1. Advances in statistical pattern recognition.- 2. Texture subspaces.- 3. Automatic selection of a discrimination rule based upon minimization of the empirical risk.- 4. Linear models in spatial discriminant analysis.- 5. Non supervised classification tools adapted to supervised classification.- 6. The bootstrap approach to clustering.- 7. On the distribution equivalence in cluster analysis.- 8. Spatial point processes and clustering tendency in exploratory data analysis.- Probabilistic Relaxation Techniques.- 9. Relaxation labelling.- 10. Optimisation algorithms in probabilistic relaxation labelling.- 11. Feature point matching using temporal smoothness in velocity.- 12. Multiresolutional cluster segmentation using spatial context.- From Markovian to Connectionist Models.- 13. Learning the parameters of a hidden Markov random field image model: A simple example.- 14. Locating texture and object boundaries.- 15. Simulated annealing: A pedestrian review of the theory and some applications.- 16. The detection of geological fault lines in radar images.- 17. Speech recognition experiment with 10,000 words dictionary.- 18. Adaptive networks and speech pattern processing.- 19. Energy methods in connectionist modelling.- 20. Learning and associative memory.- 21. Network representations and match filters for invariant object recognition.- Graph Theory And Geometry.- 22. Problems and possible solutions in the analysis of sparse images.- 23. Stochastic geometry and perception.- 24. Computational geometry: Recent results relevant to pattern recognition.- Structural Methods.- 25. Structural methods in pattern analysis.- 26. Structural pattern recognition: A random graph approach.- 27. Inexact graph matching used in machine vision.- 28. Development of an incremental graph matching device.- Hybrid Methods And Fuzzy Sets.- 29. Hybrid methods in pattern recognition.- 30. Fuzzy sets in pattern recognition.- Knowledge-Based Recognition Techniques.- 31. Classification problem solving: A tutorial from an AI perspective.- 32. On the structure of parallel adaptive search.- 33. Three dimensional organ recognition by tomographic image analysis.- 34. Knowledge-based computer recognition of speech.- 35. Modelling (sub)string-Iength based constraints through a grammatical inference method.- Machine Vision And Image Processing.- 36. Intrinsic characteristics as the interface between CAD and machine vision systems.- 37. The tensor differential scale space representation.- 38. The application of image tensors and a new decomposition.- 39. Image understanding strategies: Application to electron microscopy.- 40. A diffusion-based description of shape.- 41. Statistical evaluation of computer extracted blood cell features for screening populations to detect leukemias.- 42. Tissue image segmentation with multicolor, multifocal algorithms.- 43. Methods for computer analysis and comparison of two-dimensional protein patterns obtained by electrophoresis.- List Of Participants.

Dati bibliografici

Titolo: Pattern Recognition Theory and Applications
Casa editrice: Springer
Data di pubblicazione: 2012
Legatura: Taschenbuch
Condizione: Neu