Gryshchuk, Vadym and Weber, Cornelius and Loo, Chu Kiong and Wermter, Stefan (2022) Go ahead and do not forget: Modular lifelong learning from event-based data. Neurocomputing, 500. pp. 1063-1074. ISSN 0925-2312, DOI https://doi.org/10.1016/j.neucom.2022.05.101.
Full text not available from this repository.Abstract
Lifelong learning is a long-standing aim for artificial agents that act in dynamic environments in which an agent needs to accumulate knowledge incrementally without forgetting previously learned representations. Contemporary methods for incremental learning from images are predominantly based on frame-based data recorded by conventional shutter cameras. We investigate methods for learning from data produced by event cameras and compare techniques to mitigate forgetting while learning incrementally. We propose a model that is composed of both, feature extraction and incremental learning. The feature extractor is utilized as a self-supervised sparse convolutional neural network that processes eventbased data. The incremental learner uses a habituation-based method that works in tandem with other existing techniques. Our experimental results show that the combination of different existing techniques with our proposed habituation-based method can help avoid catastrophic forgetting even more, while learning incrementally from the features provided by the extraction module. (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
| Item Type: | Article |
|---|---|
| Funders: | Alexander von Humboldt-Stiftung, Deutsche Forschungsgemeinschaft [Grant No; TRR169], Japan Society for the Promotion of Science |
| Uncontrolled Keywords: | Lifelong learning; Habituation; Event-based data; Bio-inspired artificial intelligence |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Artificial Intelligence |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 19 Oct 2023 03:51 |
| Last Modified: | 19 Oct 2023 03:51 |
| URI: | http://eprints.um.edu.my/id/eprint/41925 |
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