Tag: Cluster Computing

Researchers propose the ASSFL protocol, an adaptive semi-synchronous federated learning method that uses a semi-decentralized topology to improve accuracy and ...

A new detection framework called TriFocus-YOLO improves fabric defect detection accuracy and maintains real-time speed by integrating edge enhancement and ...

Researchers have introduced a new computational framework called K-GA-PSO++, designed to enhance the quality and efficiency of clustering algorithms.

MAPS-Net, a new multi-modal attention and planning network, enhances autonomous UAV thermal mapping by combining deep learning with Monte Carlo ...

Researchers operating an academic physics cluster combined real-time power tracking, renewable grid forecasts, and digital twin simulations to demonstrate practical ...

FedSPA combines Shapley-value analysis and model parameter similarity to identify malicious clients in federated learning under data poisoning attacks.

Researchers propose EMASDCS, a hybrid metaheuristic combining echo localization search and adaptive memory enhanced learning, and show competitive efficiency on ...

Researchers propose a blockchain system that rewards waste recycling and regeneration activities with Semi-Fungible Tokens under government oversight.

A new personalized federated learning framework uses Transformer-based dynamic aggregation and adaptive regularization to improve colorectal cancer CT image classification ...

A new distributed intrusion detection system uses machine learning, blockchain and collaborating fog nodes, with reported zero-day F1-score rising from ...