OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Docker-based federated learning framework design and deployment for multi-modal data stream classification
Arijit Nandi, Fatos Xhafa, Rohit Kumar
Computing (2023) Vol. 105, Iss. 10, pp. 2195-2229
Closed Access | Times Cited: 8

Showing 8 citing articles:

Intelligent architecture and platforms for private edge cloud systems: A review
Xiyuan Xu, S. R. Zang, Muhammad Bilal, et al.
Future Generation Computer Systems (2024) Vol. 160, pp. 457-471
Open Access | Times Cited: 6

Federated learning in Emotion Recognition Systems based on physiological signals for privacy preservation: a review
Neha Gahlan, Divyashikha Sethia
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 4

Enhancing Industrial Control Systems Security: Real-Time Anomaly Detection with Uncertainty Estimation
Ermiyas Birihanu Belachew, Ayyoub Soullami, Imre Lendák
Lecture notes in computer science (2025), pp. 99-114
Closed Access

A Novel Governance Framework: A Federated Learning Approach for Asthma Care in Fog, Cloud, and IoMT-Based eHealth
B D Amin, Ghalem Belalem, Benatta Dalila, et al.
Algorithms for intelligent systems (2025), pp. 57-69
Closed Access

Micro-FL: A Fault-Tolerant Scalable Microservice-Based Platform for Federated Learning
Mikael Sabuhi, Petr Musı́lek, Cor‐Paul Bezemer
Future Internet (2024) Vol. 16, Iss. 3, pp. 70-70
Open Access | Times Cited: 2

FedIBD: a federated learning framework in asynchronous mode for imbalanced data
Y. R. Hou, Li Haoyuan, Zihan Guo, et al.
Applied Intelligence (2024) Vol. 55, Iss. 2
Closed Access | Times Cited: 1

Deployment and performance monitoring of docker based federated learning framework for software defect prediction
Ruchika Malhotra, Anjali Bansal, Marouane Kessentini
Cluster Computing (2024) Vol. 27, Iss. 5, pp. 6039-6057
Closed Access

Benchmarking Federated Learning on High-Performance Computing: Aggregation Methods and Their Impact
Daniela Annunziata, Marzia Canzaniello, Marcella Savoia, et al.
(2024), pp. 207-214
Closed Access

Page 1

Scroll to top