An Optimized Multi-Task Learning Model for Disaster Classification and Victim Detection in Federated Learning Environments-Reference-Cited by-同舟云学术

An Optimized Multi-Task Learning Model for Disaster Classification and Victim Detection in Federated Learning Environments

Published:2022 Issue: Volume:10 Page:115930-115944
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Wong Yi Jie¹^ORCID,Tham Mau-Luen¹^ORCID,Kwan Ban-Hoe²^ORCID,Gnanamuthu Ezra Morris Abraham¹^ORCID,Owada Yasunori³

Affiliation:

1. Department of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Selangor, Malaysia

2. Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Selangor, Malaysia

3. Resilient ICT Research Center, Network Research Institute, National Institute of Information and Communications Technology (NICT), Tokyo, Japan

Funder

ASEAN IVO (https://www.nict.go.jp/en/asean_ivo/index.html) project, Context-Aware Disaster Mitigation using Mobile Edge Computing and Wireless Mesh Network

NICT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09933763.pdf?arnumber=9933763

Reference64 articles.

1. Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor Segmentation

2. Multi-Task Self-Supervised Object Detection via Recycling of Bounding Box Annotations

3. UAV-based Localization of Mobile Phones for Search and Rescue Applications

4. A Smart UAV-Femtocell Data Sensing System for Post-Earthquake Localization of People

5. Audio-Processing-Based Human Detection at Disaster Sites With Unmanned Aerial Vehicle

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