Feature Coding for Image Representation and Recognition (Record no. 57727)

000 -LEADER
fixed length control field 03138nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-662-45000-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112227.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 150105s2014 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783662450000
-- 978-3-662-45000-0
082 04 - CLASSIFICATION NUMBER
Call Number 006.4
100 1# - AUTHOR NAME
Author Huang, Yongzhen.
245 10 - TITLE STATEMENT
Title Feature Coding for Image Representation and Recognition
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 74 p. 36 illus., 32 illus. in color.
490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Computer Science,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 1. Introduction -- 2. Taxonomy -- 3. Representative Feature Coding Algorithms -- 4. Evolution of Feature Coding -- 5. Experimental Study of Feature Coding -- 6. Enhancement via Integrating Spatial Information -- 7. Enhancement via Integrating High Order Coding Information -- 8. Conclusion.
520 ## - SUMMARY, ETC.
Summary, etc This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4) Discuss the applications of feature coding in different visual tasks, analyze the influence of some key factors in feature coding with intensive experimental studies; (5) Provide the suggestions of how to apply different feature coding methods and forecast the potential directions for future work on the topic. It is suitable for students, researchers, practitioners interested in object recognition.
700 1# - AUTHOR 2
Author 2 Tan, Tieniu.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-662-45000-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2014.
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-- text
-- txt
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-- computer
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-- rdamedia
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-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Algorithms.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Image processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern recognition.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Image Processing and Computer Vision.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Algorithm Analysis and Problem Complexity.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2191-5768
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-- ZDB-2-SCS

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