Comparison of sparse coding and kernel methods for histopathological classification of gliobastoma multiforme.
Ju HanHang ChangLeandro A. LossKai ZhangFrederick L. BaehnerJoe W. GrayPaul T. SpellmanBahram ParvinPublished in: ISBI (2011)
Keyphrases
- kernel methods
- sparse coding
- feature space
- dictionary learning
- support vector
- image classification
- support vector machine
- machine learning
- sparse representation
- kernel function
- unsupervised learning
- natural images
- classification accuracy
- multiple kernel learning
- linear combination
- learning problems
- kernel learning
- feature extraction
- pattern recognition
- feature vectors
- image representation
- image patches
- high dimensional
- kernel matrix
- feature set
- text classification
- reproducing kernel hilbert space
- decision trees
- kernel machines
- visual words
- svm classifier
- generative model
- higher order
- supervised learning
- training set