Saltus–“A Sudden Transition” Empowered by Federated Learning for Efficient Big Data Handling in Multimedia Sensor Networks-Reference-Cited by-同舟云学术

Saltus–“A Sudden Transition” Empowered by Federated Learning for Efficient Big Data Handling in Multimedia Sensor Networks

Published:2024 Issue: Volume:12 Page:88620-88633
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Remya S.¹^ORCID,Pillai Manu J.²^ORCID,Sha Akhbar¹^ORCID,Rajan Ginu³^ORCID,Rama Subbareddy Somula⁴,Cho Yongyun⁵^ORCID

Affiliation:

1. School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kollam, Kerala, India

2. Department of Computer Science and Engineering, TKM College of Engineering, Kollam, Kerala, India

3. Centre for Engineering Research in Intelligent Sensors and Systems, Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, U.K.

4. Department of Information Technology, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering Technology, Hyderabad, Telangana, India

5. Department of Information and Communication Engineering, Sunchon National University, Jeollanam-do, Suncheon, South Korea

Funder

Innovative Human Resource Development for Local Intellectualization Program through the Institute of Information and Communications Technology Planning and Evaluation

Korean Government, Ministry of Science and ICT (MSIT), South Korea

MSIT through the Information Technology Research Center (ITRC) Support Program Supervised by the Institute for Information and Communications Technology Planning and Evaluation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10570166.pdf?arnumber=10570166

Reference41 articles.

1. Predictive Analysis for Healthcare Sector Using Big data Technology

2. Amrita-CEN-SentiDB: Twitter Dataset for Sentimental Analysis and Application of Classical Machine Learning and Deep Learning

3. Performance Analysis of Water Quality Monitoring System in IoT Using Machine Learning Techniques

4. Intrusion Detection in SDN-Based Networks: Deep Recurrent Neural Network Approach

5. Cross-domain representation-learning framework with combination of class-separate and domain-merge objectives