LNL+K: Enhancing Learning with Noisy Labels Through Noise Source Knowledge Integration

Documenti analoghi

• Noise-Aware Generalization: Robustness to In-Domain Noise and Out-of-Domain Generalization
  di: Wang, Siqi, et al.
  Pubblicazione: (2025)
• Enhancing Virtual Try-On with Synthetic Pairs and Error-Aware Noise Scheduling
  di: Li, Nannan, et al.
  Pubblicazione: (2025)
• FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels
  di: Li, Jichang, et al.
  Pubblicazione: (2023)
• Noisy Label Classification using Label Noise Selection with Test-Time Augmentation Cross-Entropy and NoiseMix Learning
  di: Lee, Hansang, et al.
  Pubblicazione: (2022)
• Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers
  di: Pham, Chau, et al.
  Pubblicazione: (2024)