A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption-Reference-Cited by-同舟云学术

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A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption

Published:2024-05-12 Issue: Volume:1710 Page:1-8
ISSN:
Container-title:2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)
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Author:

Rüb Marcus¹,Tuchel Philipp¹,Sikora Axel²,Mueller-Gritschneder Daniel³

Affiliation:

1. Software Solutions / Artificial intelligence Hahn-Schickard,Villingen-Schwenningen,Germany

2. Institute of Reliable Embedded Systems and Communication Electronics (ivESK) Offenburg University of Applied Sciences,Offenburg,Germany

3. Technical University of Munich,Electronic Design Automation,Munich,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10639954/10639940/10639989.pdf?arnumber=10639989

Reference13 articles.

1. Overcoming catastrophic forgetting in neural networks

2. Learning without Forgetting

3. Core50: a new dataset and benchmark for continuous object recognition;Lomonaco

4. Data-free knowledge distillation for deep neural networks;Lopes;arXiv preprint arXiv,2017

5. Lifelong Learning of Spatiotemporal Representations With Dual-Memory Recurrent Self-Organization

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