Download or read book Quelques mod les math matiques et algorithmes rapides pour le traitement d images written by Rémy Abergel and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dans cette thèse, nous nous intéressons à différents modèles mathématiques de traitement d'images numériques dits de bas niveau. Si l'approche mathématique permet d'établir des modèles innovants pour traiter les images, ainsi que l ́étude rigoureuse des propriétés des images qu'ils produisent, ils impliquent parfois l'utilisation d'algorithmes très consommateurs de temps de calcul et de mémoire. Aussi, nous portons un soin particulier au développement d'algorithmes rapides à partir des modèles mathématiques considérés. Nous commençons par effectuer une présentation synthétique des méthodes mathématiques basées sur la dualité de Legendre-Fenchel permettant la minimisation d'énergies faisant intervenir la variation totale, fonctionnelle convexe nondifférentiable, ceci afin d'effectuer divers traitements sur les images numériques. Nous étudions ensuite un modèle de discrétisation de la variation totale inspiré de la théorie de l'échantillonnage de Shannon. Ce modèle, appelé ≪ variation totale Shannon ≫ permet un contrôle fin de la régularité des images sur une échelle sous-pixellique. Contrairement aux modèles de discrétisation classiques qui font appel à des schémas aux différences finies, nous montrons que l'utilisation de la variation totale Shannon permet de produire des images pouvant être facilement interpolées. Nous montrons également que la variation totale Shannon permet un gain conséquent en matière d'isotropie et ouvre la porte à de nouveaux modèles mathématiques de restauration. Après cela, nous proposons une adaptation du modèle TV-ICE (Iterated Conditional Expectations, proposé en 2014 par Louchet et Moisan) au cas du débruitage d'images en présence de bruit de Poisson. Nous démontrons d'une part que le schéma numérique issu de ce modèle consiste en un schéma de point fixe dont la convergence est linéaire, d'autre part que les images ainsi produites ne présentent pas d'effet de marche d'escalier (staircasing), contrairement aux images obtenues avec l'approche plus classique dite du maximum a posteriori. Nous montrons également que le modèle Poisson TV-ICE ainsi établi repose sur l'évaluation numérique d'une fonction gamma incomplète généralisée nécessitant une prise en compte fine des erreurs numériques inhérentes au calcul en précision finie et pour laquelle nous proposons un algorithme rapide permettant d'atteindre une précision quasi-optimale pour une large gamme de paramètres. Enfin, nous reprenons les travaux effectués par Primet et Moisan en 2011 concernant l'algorithme astre (A contrario Smooth TRajectory Extraction) dédié à la détection de trajectoires régulières à partir d'une séquence de nuages de points, ces points étant considérés comme issus d'une détection préalable dans une 3 séquence d'images. Si l'algorithme astre permet d'effectuer une détection optimale des trajectoires régulières au sens d'un critère a contrario, sa complexité en O(K2) (où K désigne le nombre d'images de la séquence) s'avère être rédhibitoire pour les applications nécessitant le traitement de longues séquences. Nous proposons une variante de l'algorithme astre appelée cutastre qui préserve les performances de l'algorithme astre ainsi que certaines de ses propriétés théoriques, tout en présentant une complexité en O(K).
Download or read book Introduction au traitement math matique des images m thodes d terministes written by Maïtine Bergounioux and published by Springer. This book was released on 2015-02-20 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ce cours est une introduction au traitement d'image mathématique déterministe. Les principales problématiques en traitement et analyse d’image y sont présentées: débruitage/filtrage/restauration, segmentation, rehaussement/défloutage, ainsi qu’un aperçu de quelques techniques d’acquisition. Les méthodes mathématiques utilisées ont essentiellement déterministes : transformation de Fourier, ondelettes, équations aux dérivées partielles, morphologie mathématique et méthodes variationnelles. Quelques applications y sont brièvement présentées pour illustrer le propos : la stéganographie, la compression et l’inpainting (ou désocclusion). Le livre comprend également un rappel des principales notions mathématiques utilisées (il se veut auto-suffisant) et la bibliographie abondante doit permettre au lecteur d’approfondir les techniques qui l’intéressent. Cet ouvrage s’adresse à des étudiants de MASTER, élèves-ingénieurs ou chercheurs désireux de comprendre ou d’approfondir les techniques mathématiques de base en traitement et analyse d’image. This course is an introduction to deterministic mathematical image processing. The main issues in processing and image analysis are presented: denoising, filtering, restoration, segmentation, enhancement and deblurring.There is also an overview of some acquisition techniques. Mathematical methods are essentially deterministic: Fourier transform, wavelets, partial differential equations, mathematical morphology and variational methods. Some applications are briefly presented to illustrate the topic, such as steganography, compression and inpainting. This self-contained book also includes a recap of the basic mathematical concepts used, and the extensive bibliography will enable readers to develop their skills. This book is intended for masters students, engineering students and researchers wanting to comprehend or deepen their understanding of thebasic mathematical techniques in processing and image analysis.
Download or read book Algorithmes pour la synth se d images et l animation 3D written by Rémy Malgouyres and published by . This book was released on 2002 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cinéma, publicité, jeux vidéos... L'infographie est aujourd'hui omniprésente dans tous les métiers de l'image. La qualité des images générées avec des ordinateurs dépend de nombreux paramètres tels que la justesse de la modélisation géométrique des objets représentés, le calcul des parties cachées ou la représentation des éclairages. Ce cours est une introduction aux algorithmes qui permettent la modélisation en 3D. Supposant étonnamment peu de prérequis, il fait le tour des modèles et techniques incontournables du domaine : Infographie 2D : tracé de droites, remplissage de polygones, fenêtrage ; Modélisation géométrique : construction des courbes, des surfaces complexes ; Affichage interactif : élimination des parties cachées, modèles d'illumination, textures ; Navigation : déplacement d'une caméra dans une scène 3D ; Rendu réaliste : lancer de rayons, transparence ; Techniques avancées : accélération et optimisation, échantillonnage stochastique. Ce livre permet une compréhension complète de ces modèles et algorithmes, avec des rappels de notions mathématiques et de nombreux exercices corrigés. Il est destiné aux étudiants de DUT d'infographie et de deuxième cycle d'infographie et d'informatique. Un guide et un support logiciel sont disponibles sur le site web de l'auteur.
Download or read book Conception d algorithmes paralleles pour le traitement d images utilisant la morphologie mathematique Application a la segmentation d images written by Christophe Laurent and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Local Approximation Techniques in Signal and Image Processing written by Vladimir I︠A︡kovlevich Katkovnik and published by SPIE-International Society for Optical Engineering. This book was released on 2006 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with a wide class of novel and efficient adaptive signal processing techniques developed to restore signals from noisy and degraded observations. These signals include those acquired from still or video cameras, electron microscopes, radar, X-rays, or ultrasound devices, and are used for various purposes, including entertainment, medical, business, industrial, military, civil, security, and scientific. In many cases useful information and high quality must be extracted from the imaging. However, often raw signals are not directly suitable for this purpose and must be processed in some way. Such processing is called signal reconstruction. This book is devoted to a recent and original approach to signal reconstruction based on combining two independent ideas: local polynomial approximation and the intersection of confidence interval rule.
Download or read book Predicting Structured Data written by Neural Information Processing Systems Foundation and published by MIT Press. This book was released on 2007 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.
Download or read book Dynamique Non lin aire Et Le Chaos written by and published by . This book was released on 1993 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Invitation to Statistics in Wasserstein Space written by Victor M. Panaretos and published by Springer Nature. This book was released on 2020-03-10 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation. Further to reviewing state-of-the-art aspects, it also provides an accessible introduction to the fundamentals of this current topic, as well as an overview that will serve as an invitation and catalyst for further research. Statistics in Wasserstein spaces represents an emerging topic in mathematical statistics, situated at the interface between functional data analysis (where the data are functions, thus lying in infinite dimensional Hilbert space) and non-Euclidean statistics (where the data satisfy nonlinear constraints, thus lying on non-Euclidean manifolds). The Wasserstein space provides the natural mathematical formalism to describe data collections that are best modeled as random measures on Euclidean space (e.g. images and point processes). Such random measures carry the infinite dimensional traits of functional data, but are intrinsically nonlinear due to positivity and integrability restrictions. Indeed, their dominating statistical variation arises through random deformations of an underlying template, a theme that is pursued in depth in this monograph.
Download or read book General Orthogonal Polynomials written by Herbert Stahl and published by Cambridge University Press. This book was released on 1992-04-24 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: An encyclopedic presentation of general orthogonal polynomials, placing emphasis on asymptotic behaviour and zero distribution.
Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.
Download or read book Quantum Mechanics Volume 3 written by Claude Cohen-Tannoudji and published by John Wiley & Sons. This book was released on 2019-12-16 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new, third volume of Cohen-Tannoudji's groundbreaking textbook covers advanced topics of quantum mechanics such as uncorrelated and correlated identical particles, the quantum theory of the electromagnetic field, absorption, emission and scattering of photons by atoms, and quantum entanglement. Written in a didactically unrivalled manner, the textbook explains the fundamental concepts in seven chapters which are elaborated in accompanying complements that provide more detailed discussions, examples and applications. * Completing the success story: the third and final volume of the quantum mechanics textbook written by 1997 Nobel laureate Claude Cohen-Tannoudji and his colleagues Bernard Diu and Franck Laloë * As easily comprehensible as possible: all steps of the physical background and its mathematical representation are spelled out explicitly * Comprehensive: in addition to the fundamentals themselves, the books comes with a wealth of elaborately explained examples and applications Claude Cohen-Tannoudji was a researcher at the Kastler-Brossel laboratory of the Ecole Normale Supérieure in Paris where he also studied and received his PhD in 1962. In 1973 he became Professor of atomic and molecular physics at the Collège des France. His main research interests were optical pumping, quantum optics and atom-photon interactions. In 1997, Claude Cohen-Tannoudji, together with Steven Chu and William D. Phillips, was awarded the Nobel Prize in Physics for his research on laser cooling and trapping of neutral atoms. Bernard Diu was Professor at the Denis Diderot University (Paris VII). He was engaged in research at the Laboratory of Theoretical Physics and High Energy where his focus was on strong interactions physics and statistical mechanics. Franck Laloë was a researcher at the Kastler-Brossel laboratory of the Ecole Normale Supérieure in Paris. His first assignment was with the University of Paris VI before he was appointed to the CNRS, the French National Research Center. His research was focused on optical pumping, statistical mechanics of quantum gases, musical acoustics and the foundations of quantum mechanics.
Download or read book The Nature of Statistical Learning Theory written by Vladimir Vapnik and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.
Download or read book Combinatorial Physics written by Adrian Tanasa and published by Oxford University Press. This book was released on 2021 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of the book is to use combinatorial techniques to solve fundamental physics problems, and vice-versa, to use theoretical physics techniques to solve combinatorial problems.
Download or read book Semi Infinite Programming written by Rembert Reemtsen and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semi-infinite programming (briefly: SIP) is an exciting part of mathematical programming. SIP problems include finitely many variables and, in contrast to finite optimization problems, infinitely many inequality constraints. Prob lems of this type naturally arise in approximation theory, optimal control, and at numerous engineering applications where the model contains at least one inequality constraint for each value of a parameter and the parameter, repre senting time, space, frequency etc., varies in a given domain. The treatment of such problems requires particular theoretical and numerical techniques. The theory in SIP as well as the number of numerical SIP methods and appli cations have expanded very fast during the last years. Therefore, the main goal of this monograph is to provide a collection of tutorial and survey type articles which represent a substantial part of the contemporary body of knowledge in SIP. We are glad that leading researchers have contributed to this volume and that their articles are covering a wide range of important topics in this subject. It is our hope that both experienced students and scientists will be well advised to consult this volume. We got the idea for this volume when we were organizing the semi-infinite pro gramming workshop which was held in Cottbus, Germany, in September 1996.
Download or read book The Math Olympian written by Richard Hoshino and published by FriesenPress. This book was released on 2015-01-26 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: BETHANY MACDONALD HAS TRAINED SIX LONG YEARS FOR THIS MOMENT. SHE'LL TRY TO SOLVE FIVE QUESTIONS IN THREE HOURS, FOR ONE IMPROBABLE DREAM. THE DREAM OF REPRESENTING HER COUNTRY, AND BECOMING A MATH OLYMPIAN. As a small-town girl in Nova Scotia bullied for liking numbers more than boys, and lacking the encouragement of her unsupportive single mother who frowns at her daughter's unrealistic ambition, Bethany's road to the International Math Olympiad has been marked by numerous challenges. Through persistence, perseverance, and the support of innovative mentors who inspire her with a love of learning, Bethany confronts these challenges and develops the creativity and confidence to reach her potential. In training to become a world-champion "mathlete", Bethany discovers the heart of mathematics - a subject that's not about memorizing formulas, but rather about problem-solving and detecting patterns to uncover truth, as well as learning how to apply the deep and unexpected connections of mathematics to every aspect of her life, including athletics, spirituality, and environmental sustainability. As Bethany reflects on her long journey and envisions her exciting future, she realizes that she has shattered the misguided stereotype that only boys can excel in math, and discovers a sense of purpose that through mathematics, she can and she will make an extraordinary contribution to society.
Download or read book Ventricular Wall Motion written by Ulrich Sigwart and published by Thieme-Stratton Corporation. This book was released on 1984 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Reinforcement Learning second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
