GMM-IL: Image Classification using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes.
Penny JohnstonKeiller NogueiraKevin SwinglerPublished in: CoRR (2022)
Keyphrases
- sample size
- probabilistic model
- image classification
- small sample
- mixture model
- gaussian mixture model
- expectation maximization
- random sample
- small sample size
- model selection
- random sampling
- finite sample
- upper bound
- statistical power
- feature extraction
- graphical models
- small samples
- statistical tests
- covariance matrix
- generative model
- variance reduction
- computer vision
- bayesian networks
- experimental design
- bayesian inference
- worst case
- image representation
- em algorithm
- image features
- hidden variables
- confidence intervals
- learning algorithm
- information criterion
- random samples
- feature vectors
- structure learning
- conditional probabilities
- cross validation
- language model
- statistical analysis
- maximum likelihood