Computational Science and Technology
7th ICCST 2020, Pattaya, Thailand, 29-30 August, 2020
Published on 16. March 2021
Book
Hardback
XIII, 585 pages
978-981-334-068-8 (ISBN)
Description
This book gathers the proceedings of the Seventh International Conference on Computational Science and Technology 2020 (ICCST 2020), held in Pattaya, Thailand, on 29-30 August 2020. The respective contributions offer practitioners and researchers a range of new computational techniques and solutions, identify emerging issues, and outline future research directions, while also showing them how to apply the latest large-scale, high-performance computational methods.
More details
Series
Edition
2021 ed.
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Illustrations
146 farbige Abbildungen, 75 s/w Abbildungen
XIII, 585 p. 221 illus., 146 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 36 mm
Weight
1166 gr
ISBN-13
978-981-334-068-8 (9789813340688)
DOI
10.1007/978-981-33-4069-5
Schweitzer Classification
Other editions
Additional editions
Rayner Alfred | Hiroyuki Iida | Haviluddin Haviluddin
Computational Science and Technology
7th ICCST 2020, Pattaya, Thailand, 29-30 August, 2020
Book
03/2022
Springer
€106.99
Shipment within 3-4 weeks
Rayner Alfred | Hiroyuki Iida | Haviluddin Haviluddin
Computational Science and Technology
7th ICCST 2020, Pattaya, Thailand, 29-30 August, 2020
E-Book
03/2021
1st Edition
Springer
€96.29
Available for download
Persons
Content
Building a Knowledge Graph of Vietnam Tourism from Text.- Technology Adoption Models: Users' Online Social Media Behavior Towards Visual Information.- A Pedagogical Framework with Integration of TPACK for Mobile Interactive System in Teaching Mathematics.- Towards Palm Bunch Ripeness Classification using Colour and Canny Edge Detection.- Attention Models for Sentiment Analysis using Objectivity and Subjectivity Word Vectors.- A Question-Answering System that Can Count.- Contactless Patient Authentication for Registration Using Face Recognition Technology.- Drawing and Recognising Simple Shapes with Real-Time Feedback Using Pattern Recognition.- Information Technology Students' Preferences on Blended Learning.- Improved Facial Recognition Algorithms based on Dragonfly and Grasshopper Optimization.