Combining support vector machine learning with the discrete cosine transform in image compression.
Jonathan RobinsonVojislav KecmanPublished in: IEEE Trans. Neural Networks (2003)
Keyphrases
- image compression
- machine learning
- support vector
- support vector machine
- kernel methods
- feature selection
- vector quantization
- compression scheme
- compressed images
- pattern recognition
- decision trees
- wavelet transform
- reconstructed image
- learning machines
- subband
- machine learning algorithms
- generalization ability
- compression ratio
- svm classifier
- learning algorithm
- logistic regression
- low bit rate
- progressive transmission
- kernel function
- data mining
- knowledge acquisition
- dct coefficients
- image processing
- explanation based learning
- discrete cosine transform
- hyperplane
- computer science
- compression algorithm
- inductive logic programming
- learning problems
- learning tasks
- data analysis
- classification accuracy
- natural language processing
- radial basis function
- reinforcement learning
- training data
- feature extraction
- binary classification
- support vectors
- active learning
- artificial intelligence
- text classification
- neural network