Machine learning and image processing in astronomy with sparse data sets.
John JenkinsonArtyom M. GrigoryanMehdi HajinorooziRaquel Diaz HernandezHayde Peregrina-BarretoAriel Ortiz EsquivelLeopoldo Altamirano RoblesVahram ChavushyanPublished in: SMC (2014)
Keyphrases
- machine learning
- image processing
- data sets
- pattern recognition
- computer vision
- machine learning methods
- speech processing
- sparse data
- high dimensional
- sparse principal component analysis
- real world data sets
- image processing algorithms
- denoising
- natural language processing
- multiscale
- feature selection
- database
- sparse representation
- signal processing
- edge detection
- machine vision
- benchmark data sets
- image analysis
- sparse coding
- image denoising
- high resolution
- supervised learning
- decision trees
- text mining
- data mining
- computer graphics
- image enhancement
- data collection
- image restoration
- compressive sensing
- real world
- learning algorithm
- artificial intelligence
- natural language
- input data
- data streams
- data analysis
- support vector machine
- digital image processing
- training data
- neural network
- machine intelligence
- feature extraction
- machine learning approaches
- scientific data
- machine learning algorithms
- knowledge representation
- knowledge discovery
- information extraction
- image registration
- model selection
- high dimensional data
- synthetic data