Table 1 Representative algorithms in ML and DL
From: Application of machine learning in ophthalmic imaging modalities
AI Techniques | Classification | Algorithms |
|---|---|---|
Conventional Machine learning | Supervised learning | SVM, Linear Regression, Logistic Regression, RF, KNN, Naïve Bayesian, Decision Tree, AdaBoost, Neural network methods |
Unsupervised learning | Principal component analysis, K-means, Expectation-maximization, Mean shift, Hierarchical clustering, Affinity propagation, Iterative self-organizing data, fuzzy C-means systems | |
Reinforcement learning | Q-learning, Temporal difference learning, State-Action-Reward-State-Action, Teaching-Box systems, Maja systems | |
Deep learning | DBN | Convolutional deep belief network, Conditional restricted Boltzmann machine |
CNN | AlexNet, GoogleNet, Visual geometry group network (VGG), Deep Residual Learning, Inception v4 (v2, v3), Restnet-152 (34,50,101), LeNet | |
RNN | Bidirectional RNN, Long short-term memory |