1 code implementation • 22 Jan 2024 • Yang Li, Xing Zhang, Bo Lei, Qianying Zhao, Min Wei, Zheyan Qu, Wenbo Wang
Simulation results show that the performance of the proposed algorithms is comparable to that of the exhaustive search method, and the deep learning-based algorithm significantly reduces the execution time of the algorithm.
no code implementations • 28 Nov 2023 • Yizhuo Cai, Bo Lei, Qianying Zhao, Jing Peng, Min Wei, Yushun Zhang, Xing Zhang
In this paper, to improve the communication efficiency of federated learning in complex networks, we study the communication efficiency optimization of federated learning for computing and network convergence of 6G networks, methods that gives decisions on its training process for different network conditions and arithmetic power of participating devices in federated learning.
no code implementations • 28 May 2020 • Elizabeth A. Holm, Ryan Cohn, Nan Gao, Andrew R. Kitahara, Thomas P. Matson, Bo Lei, Srujana Rao Yarasi
The characterization and analysis of microstructure is the foundation of microstructural science, connecting the materials structure to its composition, process history, and properties.
1 code implementation • 6 Mar 2020 • Liyuan Wang, Bo Lei, Qian Li, Hang Su, Jun Zhu, Yi Zhong
Continual acquisition of novel experience without interfering previously learned knowledge, i. e. continual learning, is critical for artificial neural networks, but limited by catastrophic forgetting.
no code implementations • 15 Jul 2019 • Haisheng Fu, Feng Liang, Bo Lei, Nai Bian, Qian Zhang, Mohammad Akbari, Jie Liang, Chengjie Tu
Recently deep learning-based methods have been applied in image compression and achieved many promising results.
no code implementations • 3 Jul 2019 • Nai Bian, Feng Liang, Haisheng Fu, Bo Lei
In this paper, we propose a deep convolutional autoencoder compression network for face recognition tasks.
3 code implementations • 4 May 2018 • Brian L. DeCost, Bo Lei, Toby Francis, Elizabeth A. Holm
We apply a deep convolutional neural network segmentation model to enable novel automated microstructure segmentation applications for complex microstructures typically evaluated manually and subjectively.