Structural, Syntactic, and Statistical Pattern Recognition (Paperback)

Xiao Bai

ISBN 10: 3319977849 / ISBN 13: 9783319977843

Published by Springer International Publishing AG, Cham, 2018

About this Item

Paperback. This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018.The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods. This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018.The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783319977843

Bibliographic Details

• Title: Structural, Syntactic, and Statistical Pattern Recognition (Paperback)
• Publisher: Springer International Publishing AG, Cham
• Publication Date: 2018
• Language: English
• ISBN 10: 3319977849
• ISBN 13: 9783319977843
• Binding: Paperback
• Condition: new

About this title

Synopsis

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018.

The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods.