Open Access
| Issue |
JNWPU
Volume 41, Number 2, April 2023
|
|
|---|---|---|
| Page(s) | 303 - 309 | |
| DOI | https://doi.org/10.1051/jnwpu/20234120303 | |
| Published online | 07 June 2023 | |
- LIU Y, SCHIELE B, SUN Q. Adaptive aggregation networks for class-incremental learning[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021: 2544–2553 [Google Scholar]
- ZHANG Zhimin. The study of classification based on incremental learning[D]. Guangzhou: South China University of Technology, 2010 (in Chinese) [Google Scholar]
- LI Z, HOIEM D. Learning without forgetting[J]. IEEE Trans on Pattern Analysis & Machine Intelligence, 2017, 40(12): 2935–2947 [Google Scholar]
- KIRKPATRICK J, PASCANU R, RABINOWITZ N, et al. Overcoming catastrophic forgetting in neural networks[J]. Proceedings of the National Academy of Sciences, 2017, 114(13): 3521–3526 [Article] [Google Scholar]
- SHIN H, LEE J K, KIM J, et al. Continual learning with deep generative replay[J]. Advances in Neural Information Processing Systems, 2017, 302994–3003 [Google Scholar]
- CHEN Yule, LI Bo, LIANG Hong, et al. Research on sonar image few-shot classification based on deep learning[J]. Journal of Northwestern Polytechnical University, 2022, 40(4): 739–745 [Article] (in Chinese) [CrossRef] [EDP Sciences] [Google Scholar]
- SHENG Ziqi, HUO Guanying. Detection of underwater mine target in sidescan sonar image based on sample simulation and transfer learning[J]. CAAI Transactions on Intelligent Systems, 2021, 16(2): 385–392 [Article] (in Chinese) [Google Scholar]
- KINGMA D P, WELLING M. Auto-encoding variational Bayes[C]//International Conference on Learning Representatio-ns, 2014 [Google Scholar]
- TANG T, DENG C, HUANG G B. Extreme learning machine for multilayer perceptron[J]. IEEE Trans on Neural Networks and Leorning Systems, 2016, 27(4): 809–821 [Article] [Google Scholar]
- BOND-TAYLOR S, LEACH A, LONG Y, et al. Deep generative modelling: a comparative review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2022, 44(11): 7327–7347 [Google Scholar]
- RADFORD A, METZ L, CHINTALA S. Unsupervised representation learning with deep convolutional generative adversarial networks[C]//International Conference on Learning Representations, 2016 [Google Scholar]
- LECUN Y, BENGIO Y, HINTON G E, et al. Deep learning[J]. Nature, 2015, 521(7553436–444 [Article] [CrossRef] [PubMed] [Google Scholar]
- KRIZHEVSKY A, SUTSKEVER I, HINTON G. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 2017, 60(6): 84–90 [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.