Catalogue Bibliothèque de L'IMIST/CNRST › Résultats de la recherche pour 'ccl=su:Pattern recognition systems'

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		Computational intelligence and pattern analysis in biology informatics Publication : Hoboken, N.J. John Wiley and Sons 2010 . xix, 372 pages , "Computational Intelligence (CI) is a successor of artificial intelligence combining elements of learning, adaptation, evolution and logic to create programs that are, in some sense, intelligent. CI exhibits an ability to learn or deal with new situations, such that the system is perceived to possess one or more attributes of reason. The different methodologies in CI work synergistically and provide, in one form or another, flexible information processing capabilities for handling a huge volume of real life data with noises, ambiguity, and missing values. Solving problems often involves search for useful regularities or patterns in large amounts of data. A typical characteristic of biological data is high dimensionality with low sample size. This poses grand challenges to traditional pattern analysis techniques, necessitating the development of sophisticated approaches--Provided by publisher. 25 cm. Date : 2010 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1), Réserver Ajouter au panier (Supprimer)
		Invariance, Déformations et reconnaissance de formes par Younes, Laurent. Publication : Berlin ; New York Springer 2004 . 248 p. , Cet ouvrage introduit un certain nombre de techniques disponibles pour la reconnaissance de formes planes, en mettant l'accent sur l'importance de la prise en compte des deux notions essentielles que sont l'invariance et l'analyse des déformation 24 cm. Date : 2004 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1), Réserver Ajouter au panier (Supprimer)
		Pattern theory from representation to inference par Grenander, Ulf. Publication : [S.l.] Oxford University Press, USA 2007 . 608 p. , Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computer science, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website. The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometric transformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum. Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look at inference, exploring random sampling approaches for estimation of model order and parametric representing of shapes. 25 cm. Date : 2007 Disponibilité : Exemplaires disponibles: La bibliothèque des Sciences Exactes et Naturelles (1), Réserver Ajouter au panier (Supprimer)

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