Computer vision : models, learning, and inference / Simon J.D. Prince.
Tipo de material:
TextoEditor: Cambridge : Cambridge University Press, 2012, c2017Descripción: xviii, 579 páginas : ilustracionesTipo de contenido: - texto
- no mediado
- volumen
- 1107011795
- 9781107011793
- 006.37 P954c 2017
| Tipo de ítem | Biblioteca actual | Colección | Signatura topográfica | Estado | Notas | Fecha de vencimiento | Código de barras | Reserva de ítems | |
|---|---|---|---|---|---|---|---|---|---|
| Libro | Biblioteca Central | Colección General | 006.37 P954c 2017 (Navegar estantería(Abre debajo)) | Disponible | GEN | 33409003024423 |
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| 006.33 R135e 1990 Expert systems : a software methodology for modern applications / | 006.337 F699w 1998 Web developer.com guide to building intelligent Web sites with JavaScript / | 006.37 B731m 2012 Making things see : 3D vision with Kinect, Processing, Arduino, and MakerBot / | 006.37 P954c 2017 Computer vision : models, learning, and inference / | 006.37 S698i 1999 Image processing, analysis, and machine vision / | 006.4 B622p 2006 Pattern recognition and machine learning / | 006.4 I61 2010 Introduction to pattern recognition : a MATLAB approach / |
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Incluye bibliografía
Machine generated contents note: Part I. Probability: 1. Introduction to probability; 2. Common probability distributions; 3. Fitting probability models; 4. The normal distribution; Part II. Machine Learning for Machine Vision: 5. Learning and inference in vision; 6. Modeling complex data densities; 7. Regression models; 8. Classification models; Part III. Connecting Local Models: 9. Graphical models; 10. Models for chains and trees; 11. Models for grids; Part IV. Preprocessing: 12. Image preprocessing and feature extraction; Part V. Models for Geometry: 13. The pinhole camera; 14. Models for transformations; 15. Multiple cameras; Part VI. Models for Vision: 16. Models for style and identity; 17. Temporal models; 18. Models for visual words; Part VII. Appendices: A. Optimization; B. Linear algebra; C. Algorithms.
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