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Author: Richard Lepage
Publisher: Montréal : École de technologie supérieure
ISBN: 9782921145404
Category : Computer vision
Languages : fr
Pages : 446
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Book Description
Author: Richard Lepage
Publisher: Montréal : École de technologie supérieure
ISBN: 9782921145404
Category : Computer vision
Languages : fr
Pages : 446
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Book Description
Author: Noreddine Gherabi
Publisher: Springer Nature
ISBN: 303072588X
Category : Computers
Languages : en
Pages : 315
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Book Description
This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.
Author: Salman Khan
Publisher: Springer Nature
ISBN: 3031018214
Category : Computers
Languages : en
Pages : 187
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Book Description
Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation. This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.
Author: Pierre Borne
Publisher: Editions OPHRYS
ISBN: 9782710808961
Category : Neural networks (Computer science)
Languages : fr
Pages : 166
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Book Description
Author: Madan M. Gupta
Publisher: New York : IEEE Press
ISBN:
Category : Computers
Languages : en
Pages : 584
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Book Description
Author: Sven Behnke
Publisher: Springer Science & Business Media
ISBN: 3540407227
Category : Computers
Languages : en
Pages : 230
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Book Description
Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.
Author: Walter Karplus
Publisher: World Scientific
ISBN: 9814505439
Category : Technology & Engineering
Languages : en
Pages : 223
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Book Description
The neural network paradigm with its various advantages might be the next promising bridge between artificial intelligence and pattern recognition that will help with the conceptualization of new computational artifacts. This volume contains ten papers which represent some of the work being done in the field, such as in computational neuroscience, pattern recognition, computational vision, and applications.
Author: Alain Faure
Publisher: Hermes Science Publications
ISBN: 9782866017187
Category :
Languages : fr
Pages : 245
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Book Description
Cybernétique des réseaux neuronaux traite d'un concept d'actualité, celui du réseau de neurones artificiels, bien adapté au traitement de l'information et des signaux. Les travaux théoriques consacrés à ces structures se développent d'une manière fulgurante depuis quelques années. L'établissement récent de modèles fondamentaux de réseaux et l'élaboration d'algorithmes assurant leur apprentissage et leur utilisation ont entraîné de nombreuses applications. Ces dernières concernent, par exemple, la reconnaissance et la classification automatique dans le domaine de l'écrit et de la parole, la prédiction de tendances boursières, la commande de processus comme le pilotage d'un aéronef ou la conduite automatique d'un véhicule... Il est apparu intéressant de présenter dans cet ouvrage les aspects les plus importants de ce domaine : les propriétés essentielles du neurone biologique, le comportement, notamment dynamique, d'assemblées de neurones. L'olfaction et la vision sont examinées ainsi que la réalisation artificielle d'aspects particuliers de ces fonctions. Après la description des principaux modèles de réseaux, sont développées des applications à caractère plus industriel, telles que l'identification et la commande. Cet ouvrage s'adresse tant aux étudiants qu'aux chercheurs et ingénieurs souhaitant actualiser leurs connaissances pour appréhender ou concevoir de nouvelles applications dans ce domaine.
Author: Yi-Tong Zhou
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 188
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Book Description
This monograph is an outgrowth of the authors' recent research on the de velopment of algorithms for several low-level vision problems using artificial neural networks. Specific problems considered are static and motion stereo, computation of optical flow, and deblurring an image. From a mathematical point of view, these inverse problems are ill-posed according to Hadamard. Researchers in computer vision have taken the "regularization" approach to these problems, where one comes up with an appropriate energy or cost function and finds a minimum. Additional constraints such as smoothness, integrability of surfaces, and preservation of discontinuities are added to the cost function explicitly or implicitly. Depending on the nature of the inver sion to be performed and the constraints, the cost function could exhibit several minima. Optimization of such nonconvex functions can be quite involved. Although progress has been made in making techniques such as simulated annealing computationally more reasonable, it is our view that one can often find satisfactory solutions using deterministic optimization algorithms.
Author: ERIC.. FEUILLEAUBOIS
Publisher:
ISBN:
Category :
Languages : fr
Pages : 195
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Book Description
NOUS PRESENTONS UNE IMPLEMENTATION ORIGINALE DE LA RECHERCHE DES MOTIFS STRUCTURAUX 3D SUR LES RESEAUX DE TYPES. POUR DETERMINER SI UN MOTIF 3D EST PRESENT DANS UNE STRUCTURE MOLECULAIRE IL FAUT TROUVER LA CORRESPONDANCE ENTRE LES ATOMES DU MOTIF ET LES ATOMES DE LA STRUCTURE QUI MINIMISE LE CRITERE DE DISSIMILARITE. C'EST UN PROBLEME D'OPTIMISATION COMBINATOIRE COMPLEXE APPARTENANT A LA CLASSE DES PROBLEMES NP-COMPLETS. NOUS PROPOSONS D'UTILISER DES HEURISTIQUES NEURONALES. POUR IMPLEMENTER CE PROBLEME SUR LES RESEAUX DE NEURONES DE TYPE HOPFIELD, NOUS CONSTRUISONS UNE FONCTION OBJECTIF QUI PENALISE LES ETATS DU RESEAU QUI NE SONT PAS ASSOCIES AVEC UNE MATRICE DE CORRESPONDANCE OU CONDUISANT A UNE FORTE VALEUR DU CRITERE DE DISSIMILARITE. LES POIDS DU RESEAU SONT ALORS CALCULES PAR L'IDENTIFICATION DE CETTE FONCTION OBJECTIF AVEC LA FONCTION D'ENERGIE DU RESEAU. AINSI QUAND LE RESEAU MINIMISE SON ENERGIE INTERNE, IL MINIMISE LA FONCTION OBJECTIF DU PROBLEME ET ABOUTIT A DES ETATS ASSOCIES A UNE SOLUTION DU PROBLEME DE RECONNAISSANCE. L'UTILISATION DES RESEAUX DE NEURONES DE TYPE HOPFIELD PRESENTE DEUX INTERETS MAJEURS: LA POSSIBILITE DE RECONNAITRE PARTIELLEMENT UN MOTIF, FONCTIONNALITE QUE L'ON NE TROUVE PAS DANS LES AUTRES ALGORITHMES DE RECHERCHE, LA PERSPECTIVE D'UNE IMPLEMENTATION MASSIVEMENT PARALLELE DU A LA NATURE INTRINSEQUEMENT PARALLELE DU FONCTIONNEMENT DES RESEAUX DE NEURONES ARTIFICIELS. LES BANQUES DE DONNEES STRUCTURALES NE STOCKENT GENERALEMENT QU'UNE CONFORMATION DE CHAQUE STRUCTURE, QUI N'EST PAS FORCEMENT CELLE CONTENANT LE MOTIF 3D RECHERCHE. SI L'ON RECONNAIT PARTIELLEMENT LE MOTIF DANS CETTE CONFORMATION DE LA STRUCTURE, ON PEUT PAR LA SUITE FAIRE UNE RECHERCHE CONFORMATIONNELLE POUR VERIFIER SI DANS UNE AUTRE CONFORMATION, LE MOTIF SERAIT PRESENT. IL EST A NOTER QUE LA PARALLELISATION D'ALGORITHME SEQUENTIEL EST GENERALEMENT TRES PROBLEMATIQUE. DISPOSER D'UN ALGORITHME PARALLELE PERMETTANT D'EFFECTUER LA MEME TACHE EST UN ATOUT CERTAIN QUAND ON VEUT UTILISER UN ORDINATEUR
