2023 Volume 40 Issue 3 Pages 3_16-3_28
In this study, we focus on incremental class continual learning for image classification, and improve the replay method that retains a part of the data given in the past and uses it to train a newly increased class. In the existing studies of replay methods, the number of data to be retained is fixed for each class. In this study, we propose a method to control the capacity of the number of core data according to the difficulty of each class, and a continual learning method CC-replay using this method. We also propose a continuous learning method, cc-replay, which uses the calculated number of core data per class. In our experiments, we evaluate the performance of cc-replay based on accuracy and training time on several benchmarks, and discuss the behavior of cc-replay when the size of the dataset and the similarity between classes are changed.