عنوان

Fundamentals of image data mining :

(Number (ISBN

3030179893

(Number (ISBN

3030179907

(Number (ISBN

3030179915

(Number (ISBN

9783030179892

(Number (ISBN

9783030179908

(Number (ISBN

9783030179915

Erroneous ISBN

3030179885

Erroneous ISBN

9783030179885

Title Proper

Fundamentals of image data mining :

General Material Designation

[Book]

Other Title Information

analysis, features, classification and retrieval /

First Statement of Responsibility

Dengsheng Zhang.

Place of Publication, Distribution, etc.

Cham, Switzerland :

Name of Publisher, Distributor, etc.

Springer,

Date of Publication, Distribution, etc.

[2019]

Specific Material Designation and Extent of Item

1 online resource

Series Title

Texts in computer science

Text of Note

Includes bibliographical references and index.

Text of Note

Part I: Preliminaries -- Fourier Transform -- Windowed Fourier Transform -- Wavelet Transform -- Part II: Image Representation and Feature Extraction -- Color Feature Extraction -- Texture Feature Extraction -- Shape Representation -- Part III: Image Classification and Annotation -- Bayesian Classification -- Support Vector Machines -- Artificial Neural Networks -- Image Annotation with Decision Trees -- Part IV: Image Retrieval and Presentation -- Image Indexing -- Image Ranking -- Image Presentation -- Appendix: Deriving the Conditional Probability of a Gaussian Process.

0

Text of Note

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. Dr. Dengsheng Zhang is a Senior Lecturer in the School of Science, Engineering and Information Technology at Federation University Australia.

Source for Acquisition/Subscription Address

Springer Nature

Stock Number

com.springer.onix.9783030179892

Title

Fundamentals of image data mining.

International Standard Book Number

9783030179885

Multimedia data mining.

Multimedia data mining.

COM012000

UYQV

UYT

UYT

Number

Edition

Class number

Book number

Zhang, Dengsheng

Date of Transaction

20200823090004.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y