4 papers
FISHER: Gradient-Decoupled Hierarchical Multi-Task Learning for Fine-Grained Aquatic Species Recognition
Phuc H. Nguyen, Ba Hung Ngo, Mai Phuong Tran +2
Fine-grained recognition of aquatic species is challenging due to subtle morphological differences and long-tailed distributions, where ultra-rare species are underrepresented. A n…
ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding
Phuc H. Nguyen, Trung T. Nguyen, Quy N. Duong +1
Semantic communication (SC) aims to reduce transmission overhead by conveying task-relevant information rather than raw data. However, existing SC approaches for video largely focu…
SC-GIR: Goal-oriented Semantic Communication via Invariant Representation Learning
Senura Hansaja Wanasekara, Van-Dinh Nguyen, Kok-Seng +3
Goal-oriented semantic communication (SC) aims to revolutionize communication systems by transmitting only task-essential information. However, current approaches face challenges s…
SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning
Dung T. Tran, Nguyen B. Ha, Van-Dinh Nguyen +1
Federated learning (FL) is a promising approach for addressing scalability and latency issues in large-scale networks by enabling collaborative model training without requiring the…