Classification of Diabetic Retinopathy Using Unlabeled Data and Knowledge Distillation.
Sajjad AbbasiMohsen HajabdollahiPejman KhadiviNader KarimiRoshanak RoshandelShahram ShiraniShadrokh SamaviPublished in: CoRR (2020)
Keyphrases
- unlabeled data
- labeled data
- semi supervised learning
- co training
- class labels
- semi supervised classification
- supervised learning
- text classification
- labeled and unlabeled data
- improve the classification accuracy
- semi supervised
- supervised learning algorithms
- training set
- labeled examples
- prior knowledge
- active learning
- classification accuracy
- label information
- labeled training data
- training data
- semi supervised learning algorithms
- knowledge base
- labeled instances
- feature extraction
- decision boundary
- transfer learning
- knowledge acquisition
- domain knowledge
- diabetic retinopathy
- decision trees
- supervised and semi supervised
- machine learning
- select relevant features
- text categorization
- expert systems
- classification algorithm
- training samples
- knowledge discovery
- learning algorithm
- feature selection
- feature space
- data points
- transductive learning
- knowledge representation
- multi view
- knowledge based systems
- unsupervised learning
- training examples
- blood vessels
- classification rules