Rethinking Noisy Label Learning in Real-world Annotation Scenarios from the Noise-type Perspective.
Renyu ZhuHaoyu LiuRunze WuMinmin LinTangjie LvChangjie FanHaobo WangPublished in: CoRR (2023)
Keyphrases
- real world
- learning systems
- learning process
- active learning
- noisy data
- learning algorithm
- wide range
- reinforcement learning
- prior knowledge
- learning problems
- background knowledge
- measurement noise
- noisy environments
- inductive inference
- image annotation
- online learning
- metadata
- machine learning
- data mining
- unsupervised learning
- learning tasks
- supervised learning
- semantic annotation
- image retrieval
- learning analytics
- noise tolerant
- neural network