DATA INCREMENTAL LEARNING IN DEEP ARCHITECTURES
Published in -, 2022
This study presents a framework for continual self-supervised learning of visual representations that prevents forgetting by combining distillation and proofreading techniques, improving the quality of learned representations even when data is fed sequentially.
Recommended citation: Alex Kameni, 2022
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