Fast image classification by boosting fuzzy classifiers.
Marcin KorytkowskiLeszek RutkowskiRafal SchererPublished in: Inf. Sci. (2016)
Keyphrases
- image classification
- svm classifier
- randomized trees
- classifier training
- ensemble learning
- weak classifiers
- weak learners
- feature selection
- boosting algorithms
- majority voting
- ensemble classifier
- boosting framework
- fuzzy logic
- fuzzy sets
- bag of words
- fuzzy rules
- improving classification accuracy
- learning algorithm
- strong classifier
- training data
- membership functions
- accurate classifiers
- image representation
- multiple classifier systems
- discriminative classifiers
- linear classifiers
- machine learning algorithms
- multiclass classification
- base classifiers
- feature extraction
- weighted voting
- training samples
- decision stumps
- naive bayes
- adaboost algorithm
- decision trees
- training set
- image features
- ensemble classification
- ensemble methods
- fuzzy clustering
- support vector
- classification trees
- classifier combination
- feature set
- cost sensitive
- machine learning
- binary classification problems
- classifier ensemble
- supervised classification
- fuzzy numbers
- machine learning methods