Content-based image classification : (Record no. 71582)

000 -LEADER
fixed length control field 05469cam a2200565Ii 4500
001 - CONTROL NUMBER
control field 9780429352928
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220531132400.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210108s2020 flu eo 000 0 eng d
040 ## - Cataloging Source
-- OCoLC-P
-- eng
-- rda
-- pn
-- OCoLC-P
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780429352928
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0429352921
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000280470
-- (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000280470
-- (electronic bk. : PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367371609
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000280715
-- (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000280713
-- (electronic bk. : EPUB)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000280593
-- (electronic bk. : Mobipocket)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000280594
-- (electronic bk. : Mobipocket)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367639280
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 036737160X
024 8# -
-- 10.1201/9780429352928
-- doi
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1229166014
Canceled/invalid control number (OCoLC)1202438953
-- (OCoLC)1202474310
-- (OCoLC)1202478154
-- (OCoLC)1202599751
-- (OCoLC)1230505336
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1229166014
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Z699.5.P53
072 #7 -
-- COM
-- 016000
-- bisacsh
072 #7 -
-- COM
-- 059000
-- bisacsh
072 #7 -
-- COM
-- 037000
-- bisacsh
072 #7 -
-- UYQ
-- bicssc
082 04 -
-- 025.040285/66
-- 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Das, Rik,
Dates associated with a name 1978-
Relator term author.
245 10 - TITLE STATEMENT
Title Content-based image classification :
Remainder of title efficient machine learning using robust feature extraction techniques /
Statement of responsibility, etc. Rik Das.
264 #1 -
-- Boca Raton, FL :
-- CRC Press,
-- 2020.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xvi, 180 pages).
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
505 0# -
-- 1.Introduction to Content Based Image Classification. 2. A Review of Hand-crafted Feature Extraction Techniques for Content Based Image Classification. 3. Content Based Feature Extraction: Color Averaging. 4. Content Based Feature Extraction: Image Binarization. 5. Content Based Feature Extraction: Image Transforms. 6. Content Based Feature Extraction: Morphological Operators.7. Content Based Feature Extraction: Texture Components. 8. Fusion Based Classification: A Comparison of Early Fusion and Late Fusion Architecture for Content Based Features. 9. Future Directions: A Journey from Handcrafted Techniques to Representation Learning. 10. WEKA: Beginners' Tutorial
520 ## -
-- Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/
588 ## -
-- OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Content-based image retrieval.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS / Computer Vision & Pattern Recognition
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS / Computer Engineering
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS / Machine Theory
Source of heading or term bisacsh
856 40 -
-- Taylor & Francis
-- https://www.taylorfrancis.com/books/9780429352928
856 42 -
-- OCLC metadata license agreement
-- http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf

No items available.

Technical University of Mombasa
Tom Mboya Street, Tudor 90420-80100 , Mombasa Kenya
Tel: (254)41-2492222/3 Fax: 2490571