Image quality assessment for machine learning tasks using meta-reinforcement learning.
Shaheer U. SaeedYunguan FuVasilis StavrinidesZachary M. C. BaumQianye YangMirabela RusuRichard E. FanGeoffrey A. SonnJ. Alison NobleDean C. BarrattYipeng HuPublished in: CoRR (2022)
Keyphrases
- learning tasks
- image quality assessment
- reinforcement learning
- function approximation
- transfer learning
- learning problems
- learning algorithm
- structural similarity
- supervised learning
- machine learning
- quality assessment
- image quality
- function approximators
- image database
- human visual system
- correlation coefficient
- learning experience
- quality metrics
- learning process
- machine learning algorithms
- human perception
- natural images
- quality evaluation
- quality measures
- visual perception
- kullback leibler divergence
- multi label
- structural information
- natural scenes
- training data
- feature selection
- text classification