The Resource Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval, by Dengsheng Zhang, (electronic resource)

Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval, by Dengsheng Zhang, (electronic resource)

Label
Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval
Title
Fundamentals of Image Data Mining
Title remainder
Analysis, Features, Classification and Retrieval
Statement of responsibility
by Dengsheng Zhang
Creator
Contributor
Author
Author
Provider
Subject
Language
eng
Summary
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
Member of
http://library.link/vocab/creatorName
Zhang, Dengsheng
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
qibh7J9fwEI
Image bit depth
0
LC call number
  • TA1637-1638
  • TA1634
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
SpringerLink
Series statement
Texts in Computer Science,
http://library.link/vocab/subjectName
  • Computer vision
  • Data mining
  • Machine learning
  • Engineering mathematics
  • Big data
  • Image Processing and Computer Vision
  • Data Mining and Knowledge Discovery
  • Machine Learning
  • Engineering Mathematics
  • Big Data
Label
Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval, by Dengsheng Zhang, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Dimensions
unknown
Extent
XXXI, 314 p. 202 illus., 117 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783030179892
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-030-17989-2
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-030-17989-2
Label
Fundamentals of Image Data Mining : Analysis, Features, Classification and Retrieval, by Dengsheng Zhang, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Dimensions
unknown
Extent
XXXI, 314 p. 202 illus., 117 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783030179892
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-030-17989-2
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-030-17989-2

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