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20192026
most cited6G Internet of Things: A Comprehensive Survey

1.4k citations · 2.3k across the 30 of their papers we have counts for

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Showing 2025Show all

10 papers · 1 filter

eess.SP2025

Leveraging Vision Transformers for Enhanced Classification of Emotions using ECG Signals

Pubudu L. Indrasiri, Bipasha Kashyap, Pubudu N. Pathirana

Biomedical signals provide insights into various conditions affecting the human body. Beyond diagnostic capabilities, these signals offer a deeper understanding of how specific org…

cs.CR2025

Domain-Adapted Granger Causality for Real-Time Cross-Slice Attack Attribution in 6G Networks

Minh K. Quan, Pubudu N. Pathirana

Cross-slice attack attribution in 6G networks faces the fundamental challenge of distinguishing genuine causal relationships from spurious correlations in shared infrastructure env…

cs.LG2025★ 42 cited

Federated Learning for Cyber Physical Systems: A Comprehensive Survey

Minh K. Quan, Pubudu N. Pathirana, Mayuri Wijayasundara +5

The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliabili…

cs.SD2025★ 1 cited

Quantum-Inspired Genetic Algorithm for Robust Source Separation in Smart City Acoustics

Minh K. Quan, Mayuri Wijayasundara, Sujeeva Setunge +1

The cacophony of urban sounds presents a significant challenge for smart city applications that rely on accurate acoustic scene analysis. Effectively analyzing these complex sounds…

cs.LG2025

Enhancing Federated Learning Through Secure Cluster-Weighted Client Aggregation

Kanishka Ranaweera, Azadeh Ghari Neiat, Xiao Liu +2

Federated learning (FL) has emerged as a promising paradigm in machine learning, enabling collaborative model training across decentralized devices without the need for raw data sh…

cs.LG2025

Adaptive Clipping for Privacy-Preserving Few-Shot Learning: Enhancing Generalization with Limited Data

Kanishka Ranaweera, Dinh C. Nguyen, Pubudu N. Pathirana +4

In the era of data-driven machine-learning applications, privacy concerns and the scarcity of labeled data have become paramount challenges. These challenges are particularly prono…