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1 X. Cai, Y. Lan, Z. Zhang, J. Wen, Z. Cui, and W. S. Zhang, "A Many-objective Optimization based Federal Deep Generation Model for Enhancing Data Processing Capability in IOT," IEEE Trans. Ind. Inf., vol. 19, no, 1, pp. 561-569, 2023./   DOI View Article
2 H. Yang, J. Yuan, C. Li et al., "BrainIoT: Brain-Like Productive Services Provisioning with Federated Learning in Industrial IoT," IEEE Internet of Things Journal, vol. 9, no. 3, pp. 2014-2024, 2022./   DOI View Article
3 H. Yang, J. Yuan, C. Li, G. Zhao, Z. Sun, Q. Yao, B. Bao, A. V. Vasilakos and J. Zhang, "BrainIoT: Brain-Like Productive Services Provisioning with Federated Learning in Industrial IoT," IEEE Internet of Things Journal, vol. 9, pp. 2014-2024, 2022./   DOI View Article
4 C. Do, T. Nguyen, and H. Nguyen, "Robust multi-sensor generalized labeled multi-Bernoulli filter," Signal Processing, vol.192, 2022./ View Article
5 Yu Ou and Lang Li, "Side-channel analysis attacks based on deep learning network," Frontiers of Computer Science, vol. 16, no. 2, pp. 1-11, September, 2022./ View Article
6 H. Zhang, "Deep Learning Applications in Simultaneous Localization and Mapping," Journal of Physics: Conference Series, vol. 2181, no. 1, pp. 012012, 2022./   DOI View Article
7 C. Xu, "Enabling Technologies for Future Mobile and Edge Networks," Transactions on Emerging Telecommunications Technologies, vol. 33, no. 3, pp. 4481, 2022./ View Article
8 P. Baskerville, D. Granziol, and P. Keating, "Appearance of Random Matrix Theory in deep learning," Physica A: Statistical Mechanics and its Applications, vol. 590, no. 15, pp. 126742, 2022./   DOI View Article
9 M. Chen, E. Lughofer, and E. Egrioglu, "Deep Learning and Intelligent System Towards Smart Manufacturing," Enterprise Information Systems, vol. 16, no. 2, pp. 189-192, 2022./   DOI View Article
10 W. Cao, C. Zheng, Z. Yan, and W. Xie, "Geometric Deep learning: progress, Applications and Challenges," Science China Information Sciences, vol. 65, no. 2, pp. 126101, 2022./   DOI View Article