Uncertainty Estimates as Data Selection Criteria to Boost Omni-Supervised Learning.
Lorenzo VenturiniAris T. PapageorghiouJ. Alison NobleAna I. L. NamburetePublished in: MICCAI (1) (2020)
Keyphrases
- selection criteria
- data sets
- training data
- supervised learning
- data structure
- knowledge discovery
- data collection
- high quality
- original data
- prior knowledge
- data mining techniques
- database
- complex data
- data distribution
- experimental data
- synthetic data
- data processing
- small number
- data points
- data analysis
- unsupervised learning
- data sources
- raw data
- uncertain data
- databases
- neural network