Robust active learning for the diagnosis of parasites
A robust active learning method, called RDS, based on a priori data organization. RDS properly balances sample diversity and uncertainty for useful sample selection. It provides high classification accuracy for the automated diagnosis of parasites. Comparisons with different clustering, classification and other literature methods. RDS was evaluated by an experienced expert in parasitology using a realistic scenario.
active learning pattern recognition automated diagnosis of intestinal parasites microscopy image analysis optimum-path forest classifiers