QA-HFL: Quality-Aware Hierarchical Federated Learning for Resource-Constrained Mobile Devices with Heterogeneous Image Quality

Documenti analoghi

• LightPure: Realtime Adversarial Image Purification for Mobile Devices Using Diffusion Models
  di: Khalili, Hossein, et al.
  Pubblicazione: (2024)
• Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
  di: Yu, Yi, et al.
  Pubblicazione: (2024)
• Privacy-Preserving Federated Learning with Verifiable Fairness Guarantees
  di: Ali, Mohammed Himayath, et al.
  Pubblicazione: (2026)
• Federated Learning for Large Models in Medical Imaging: A Comprehensive Review
  di: Sun, Mengyu, et al.
  Pubblicazione: (2025)
• VGS-ATD: Robust Distributed Learning for Multi-Label Medical Image Classification Under Heterogeneous and Imbalanced Conditions
  di: Zhao, Zehui, et al.
  Pubblicazione: (2025)