Classification of Pollen Grain Images Based on an Ensemble of Classifiers.
David Gutierrez AriasMarcos Vinicius Mussel CirneJosimar Edinson Chire SaireHélio PedriniPublished in: ICMLA (2017)
Keyphrases
- multiple classifiers
- image classification
- classifier ensemble
- final classification
- support vector
- ensemble classifier
- classification systems
- classification method
- training set
- classification algorithm
- feature selection
- combining classifiers
- ensemble learning
- object category recognition
- supervised classification
- classification models
- decision trees
- majority voting
- input image
- multiple classifier systems
- svm classifier
- object recognition
- machine learning methods
- class labels
- individual classifiers
- decision tree classifiers
- accurate classifiers
- machine learning algorithms
- discriminative classifiers
- training samples
- image retrieval
- classifier combination
- multi category
- classification accuracy
- extracted features
- generalization ability
- image features
- training data
- feature extraction
- ensemble classification
- probabilistic classifiers
- machine learning
- ensemble methods
- minimum distance classifier
- concept drifting data streams
- class conditional densities
- decision boundary
- support vector machine
- weak learners
- roc curve
- base classifiers
- highly discriminative
- binary classifiers
- combination of multiple classifiers
- accurate classification
- feature ranking
- feature set
- classification rate
- cost sensitive
- feature subset
- benchmark datasets
- support vector machine svm
- text classification