Pattern recognition : ACPR 2019 Workshops, Auckland, New Zealand, November 26, 2019, Proceedings / Michael Cree, Fay Huang, Junsong Yuan, Wei Qi Yan (eds.).
2020
TK7882.P3
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Title
Pattern recognition : ACPR 2019 Workshops, Auckland, New Zealand, November 26, 2019, Proceedings / Michael Cree, Fay Huang, Junsong Yuan, Wei Qi Yan (eds.).
ISBN
9789811536519 (electronic book)
9811536511 (electronic book)
9789811536502
9811536511 (electronic book)
9789811536502
Imprint
Singapore : Springer, 2020.
Language
English
Description
1 online resource (280 pages)
Other Standard Identifiers
10.1007/978-981-15-3651-9 doi
Call Number
TK7882.P3
Dewey Decimal Classification
006.4
Summary
This volume constitutes the refereed proceedings, presented during the ACPR 2019 Workshops, held in Auckland, New Zealand, in November 2019. The 17 full papers and 6 short papers were carefully reviewed and selected out of numerous submissions. The papers are organized according to the topics of the workshops: computer vision for modern vehicles; advances and applications on generative deep learning models; image and pattern analysis for multidisciplinary computational anatomy; multi-sensor for action and gesture recognition; towards the automatic data processing chain for airborne and spaceborne sensors.
Note
International conference proceedings.
Includes author index.
Includes author index.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Communications in computer and information science ; 1180.
Available in Other Form
Pattern Recognition : ACPR 2019 Workshops, Auckland, New Zealand, November 26, 2019, Proceedings.
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Online Access
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Table of Contents
Computer Vision for Modern Vehicles
Advances and Applications on Generative Deep Learning Models
Image and Pattern Analysis for Multidisciplinary Computational Anatomy
Multi-Sensor for Action and Gesture Recognition
Towards an Automatic Data Processing Chain for Airborne and Spaceborne Sensors.
Advances and Applications on Generative Deep Learning Models
Image and Pattern Analysis for Multidisciplinary Computational Anatomy
Multi-Sensor for Action and Gesture Recognition
Towards an Automatic Data Processing Chain for Airborne and Spaceborne Sensors.