Application of transfer learning models such as InceptionV3, Xception and DenseNet201 for feature extraction of a rebalanced 1,000 knee X-ray images taken from Osteoarthritis Initiative (OAI) dataset with 5 classes graded 0–4 according to Kellgren-Lawrence grading split into a 70/15/15 training/validation/testing split. The features extracted are subsequently fed into machine learning classifiers, namely support vector machine (SVM), random forests (RF) and logistic regression (LR). An average multiclass accuracy of 71.33% was achieved for hyperparameter fine-tuned DenseNet201-SVM model.
https://journal.ump.edu.my/mekatronika/article/view/8627/2519