Articles liés à Fundamentals of Image Data Mining: Analysis, Features,...
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval - Couverture souple
Synopsis
This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.
Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Dr. Dengsheng Zhang is a Senior Lecturer in the School of Science, Engineering and Information Technology at Federation University Australia.
---
Textbook & Academic Authors Association 2020 Most Promising New Textbook Award Winner!
The judges said:
"Fundamentals of Image Data Mining provides excellent coverage of current algorithms and techniques in image analysis. It does this using a progression of essential and novel image processing tools that give students an in-depth understanding of how the tools fit together and how to apply them to problems."
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 45,58
EUR 7,70 expédition depuis Etats-Unis vers France
Destinations, frais et délaisAutres éditions populaires du même titre
Résultats de recherche pour Fundamentals of Image Data Mining: Analysis, Features,...
Image d'archives
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science)
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. pp. 314. N° de réf. du vendeur 26380298326
Quantité disponible : 1 disponible(s)
Image d'archives
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. pp. 314. N° de réf. du vendeur 383605641
Quantité disponible : 1 disponible(s)
Image d'archives
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science)
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. pp. 314. N° de réf. du vendeur 18380298332
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Fundamentals of Image Data Mining
Edité par
Springer International Publishing, 2020
ISBN 10 : 3030179915
ISBN 13 : 9783030179915
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a complete introduction to image data mining, and a treasure trove of cutting-edge techniques in image data miningDescribes the applied mathematics and mathematical modelling in an engaging style, complete with an accessible introduction . N° de réf. du vendeur 448674290
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval
Edité par
Springer International Publishing, 2020
ISBN 10 : 3030179915
ISBN 13 : 9783030179915
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing. N° de réf. du vendeur 9783030179915
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Fundamentals of Image Data Mining
Edité par
Springer International Publishing Aug 2020, 2020
ISBN 10 : 3030179915
ISBN 13 : 9783030179915
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing. 348 pp. Englisch. N° de réf. du vendeur 9783030179915
Quantité disponible : 2 disponible(s)
Image d'archives
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval (Texts in Computer Science)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9783030179915_new
Quantité disponible : Plus de 20 disponibles
Image d'archives
Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
PF. Etat : New. N° de réf. du vendeur 6666-IUK-9783030179915
Quantité disponible : 10 disponible(s)
Image fournie par le vendeur
Fundamentals of Image Data Mining
ISBN 10 : 3030179915
ISBN 13 : 9783030179915
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image analysis and understanding, offering deep insights into areas of feature extraction, machine learning, and image retrieval. The theoretical coverage is supported by practical mathematical models and algorithms, utilizing data from real-world examples and experiments.Topics and features: describes the essential tools for image mining, covering Fourier transforms, Gabor filters, and contemporary wavelet transforms; reviews a varied range of state-of-the-art models, algorithms, and procedures for image mining; emphasizes how to deal with real image data for practical image mining; highlights how such features as color, texture, and shape can be mined or extracted from images for image representation; presents four powerful approaches for classifying image data, namely, Bayesian classification, Support Vector Machines, Neural Networks, and Decision Trees; discusses techniques for indexing, image ranking, and image presentation, along with image database visualization methods; provides self-test exercises with instructions or Matlab code, as well as review summaries at the end of each chapter.This easy-to-follow work illuminates how concepts from fundamental and advanced mathematics can be applied to solve a broad range of image data mining problems encountered by students and researchers of computer science. Students of mathematics and other scientific disciplines will also benefit from the applications and solutions described in the text, together with the hands-on exercises that enable the reader to gain first-hand experience of computing.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 348 pp. Englisch. N° de réf. du vendeur 9783030179915
Quantité disponible : 2 disponible(s)
Image d'archives
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval
Edité par
Springer-Nature New York Inc, 2020
ISBN 10 : 3030179915
ISBN 13 : 9783030179915
Neuf
Paperback
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. 348 pages. 9.25x6.10x0.82 inches. In Stock. N° de réf. du vendeur x-3030179915
Quantité disponible : 2 disponible(s)