How to scale hyperparameters for quickshift image segmentation.
Damien GarreauPublished in: CoRR (2022)
Keyphrases
- hyperparameters
- image segmentation
- model selection
- cross validation
- bayesian inference
- closed form
- random sampling
- bayesian framework
- maximum a posteriori
- em algorithm
- support vector
- gaussian process
- prior information
- incremental learning
- sample size
- noise level
- markov random field
- maximum likelihood
- gaussian processes
- expectation maximization
- regularization parameter
- incomplete data
- parameter space
- multiscale
- missing values
- parameter settings
- computer vision
- noise reduction
- level set
- machine learning
- graph cuts
- active learning
- high resolution