Pattern recognition : 7th Asian Conference, ACPR 2023, Kitakyushu, Japan, November 5-8, 2023, Proceedings. Part III / Huimin Lu, Michael Blumenstein, Sung-Bae Cho, Cheng-Lin Liu, Yasushi Yagi, Tohru Kamiya, editors.
2023
TK7882.P3
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Title
Pattern recognition : 7th Asian Conference, ACPR 2023, Kitakyushu, Japan, November 5-8, 2023, Proceedings. Part III / Huimin Lu, Michael Blumenstein, Sung-Bae Cho, Cheng-Lin Liu, Yasushi Yagi, Tohru Kamiya, editors.
ISBN
9783031476655 (electronic bk.)
3031476654 (electronic bk.)
9783031476648
3031476654 (electronic bk.)
9783031476648
Published
Cham : Springer, 2023.
Language
English
Description
1 online resource (xiii, 401 pages) : illustrations (some color).
Item Number
10.1007/978-3-031-47665-5 doi
Call Number
TK7882.P3
Dewey Decimal Classification
006.4
Summary
This three-volume set LNCS 14406-14408 constitutes the refereed proceedings of the 7th Asian Conference on Pattern Recognition, ACPR 2023, held in Kitakyushu, Japan, in November 2023. The 93 full papers presented were carefully reviewed and selected from 164 submissions. The conference focuses on four important areas of pattern recognition: pattern recognition and machine learning, computer vision and robot vision, signal processing, and media processing and interaction, covering various technical aspects.
Note
Includes author index.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed November 7, 2023).
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Series
Lecture notes in computer science ; 14408. 1611-3349
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Table of Contents
artificial intelligence
computer networks
computer science
computer systems
computer vision
databases
education
engineering
image analysis
image processing
image segmentation
internet learning
machine learning
mathematics
neural networks
object recognition
pattern recognition semantics
signal processing.
computer networks
computer science
computer systems
computer vision
databases
education
engineering
image analysis
image processing
image segmentation
internet learning
machine learning
mathematics
neural networks
object recognition
pattern recognition semantics
signal processing.