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引用“”的文章A Comprehensive Survey on Transfer Learning

标题/作者	年份
Generalizing to unseen domains: A survey on domain generalization J Wang, C Lan, C Liu, Y Ouyang, T Qin, W Lu, Y Chen, W Zeng, P Yu IEEE Transactions on Knowledge and Data Engineering	2022
Sim-to-real transfer in deep reinforcement learning for robotics: a survey W Zhao, JP Queralta, T Westerlund 2020 IEEE symposium series on computational intelligence (SSCI), 737-744	2020
Deep subdomain adaptation network for image classification Y Zhu, F Zhuang, J Wang, G Ke, J Chen, J Bian, H Xiong, Q He IEEE transactions on neural networks and learning systems 32 (4), 1713-1722	2020
Multi-task learning with deep neural networks: A survey M Crawshaw arXiv preprint arXiv:2009.09796	2020
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey S Bhattacharya, PKR Maddikunta, QV Pham, TR Gadekallu, ... Sustainable cities and society 65, 102589	2021
Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things J Zhang, D Tao IEEE Internet of Things Journal 8 (10), 7789-7817	2020
Visual prompt tuning M Jia, L Tang, BC Chen, C Cardie, S Belongie, B Hariharan, SN Lim European Conference on Computer Vision, 709-727	2022
Domain adaptation for medical image analysis: a survey H Guan, M Liu IEEE Transactions on Biomedical Engineering 69 (3), 1173-1185	2021
Escaping the big data paradigm with compact transformers A Hassani, S Walton, N Shah, A Abuduweili, J Li, H Shi arXiv preprint arXiv:2104.05704	2021
Towards out-of-distribution generalization: A survey Z Shen, J Liu, Y He, X Zhang, R Xu, H Yu, P Cui arXiv preprint arXiv:2108.13624	2021
A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges W Li, R Huang, J Li, Y Liao, Z Chen, G He, R Yan, K Gryllias Mechanical Systems and Signal Processing 167, 108487	2022
Bearing fault detection and diagnosis using case western reserve university dataset with deep learning approaches: A review D Neupane, J Seok IEEE Access 8, 93155-93178	2020
A survey on deep semi-supervised learning X Yang, Z Song, I King, Z Xu IEEE Transactions on Knowledge and Data Engineering	2022
A decade survey of transfer learning (2010–2020) S Niu, Y Liu, J Wang, H Song IEEE Transactions on Artificial Intelligence 1 (2), 151-166	2020
A review on deep learning in UAV remote sensing LP Osco, JM Junior, APM Ramos, LA de Castro Jorge, SN Fatholahi, ... International Journal of Applied Earth Observation and Geoinformation 102 …	2021
Ensemble transfer CNNs driven by multi-channel signals for fault diagnosis of rotating machinery cross working conditions Z He, H Shao, X Zhong, X Zhao Knowledge-Based Systems 207, 106396	2020
Deep learning for smart fish farming: applications, opportunities and challenges X Yang, S Zhang, J Liu, Q Gao, S Dong, C Zhou Reviews in Aquaculture 13 (1), 66-90	2021
Skin lesion segmentation and multiclass classification using deep learning features and improved moth flame optimization MA Khan, M Sharif, T Akram, R Damaševičius, R Maskeliūnas Diagnostics 11 (5), 811	2021
Machine learning for metabolic engineering: A review CE Lawson, JM Martí, T Radivojevic, SVR Jonnalagadda, R Gentz, ... Metabolic Engineering 63, 34-60	2021
Dos and don'ts of machine learning in computer security D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ... 31st USENIX Security Symposium (USENIX Security 22), 3971-3988	2022

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