A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes.
Ángel E. EstebanMiguel López-PérezAdrián ColomerMaría Á. SalesRafael MolinaValery NaranjoPublished in: Comput. Methods Programs Biomed. (2019)
Keyphrases
- gaussian processes
- gaussian process
- hyperparameters
- gaussian process regression
- decision trees
- support vector
- model selection
- object recognition
- text classification
- multi task
- feature vectors
- bayesian framework
- latent variables
- histological images
- scale space analysis
- prostate cancer
- bayesian inference
- closed form
- regression model
- feature extraction