Mobile Computing, Applications, and Services
12th EAI International Conference, MobiCASE 2021, Virtual Event, November 13-14, 2021, Proceedings
Published on 24. March 2022
Book
Paperback/Softback
XI, 145 pages
978-3-030-99202-6 (ISBN)
Description
This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2021, held in November 2021. Due to COVID-19 pandemic the conference was held virtually.
The 9 full papers were carefully reviewed and selected from 21 submissions. The papers are organized in two topical tracks: mobile application and deep learning, and mobile application with data analysis.
More details
Series
Edition
1st ed. 2022
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
13 s/w Abbildungen, 25 farbige Abbildungen
XI, 145 p. 38 illus., 25 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 9 mm
Weight
254 gr
ISBN-13
978-3-030-99202-6 (9783030992026)
DOI
10.1007/978-3-030-99203-3
Schweitzer Classification
Other editions
Additional editions
Shuiguang Deng | Albert Zomaya | Ning Li
Mobile Computing, Applications, and Services
12th EAI International Conference, MobiCASE 2021, Virtual Event, November 13-14, 2021, Proceedings
E-Book
03/2022
Springer
€69.54
Available for download
Persons
Content
Mobile Application and Deep Learning.- YOLO-RFB: An improved traffic sign detection model.- Privacy-Preserving Sharing of Mobile Sensor Data.- Service performance analysis of cloud computing server by queuing system.- CLES: A Universal Wrench for Embedded Systems Communication and Coordination.- When Neural Networks Using Different Sensors Create Similar Features.- Mobile Application with Data Analysis.- Improving Togetherness Using Structural Entropy.- Blockchain-based Group Key Agreement.- Attacking community detector: a way to mislead detector via manipulating the graph structure.- ResNet-like CNN Architecture and Saliency Map for Human Activity Recognition.