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Conference Paper
Retraining Image Classification Model with Ensemble Networks and Episodic Memories in Three Continual Learning Scenarios
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- Authors
- Soonyong Song, Heechul Bae, Hyonyoung Han, Youngsung Son
- Issue Date
- 2020-06
- Citation
- Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2020, pp.1-4
- Language
- English
- Type
- Conference Paper
- Abstract
- In this competition, we evaluated three continual learning (CL) scenarios with a CORe50 dataset. To preserve past knowledge from catastrophic forgetting, we trained classification model through multi-head and latent replay approaches. To increase classification performance, an ensemble model was implemented in feature network composed of three excellent backbone networks. Also, early stopping and learning rate scheduling schemes were applied to maximize prediction accuracy without overfitting. Our approaches showed score 0.89 by average with respect to the three scenarios in this qualification step.
- KSP Keywords
- Backbone Network, Catastrophic forgetting, Classification Performance, Classification models, Early stopping, Ensemble models, Ensemble networks, Image Classification, Learning rate, Learning scenarios, Multi-head