Zobrazeno 1 - 10
of 630
pro vyhledávání: '"Li Xiufang"'
Publikováno v:
Romanian Journal of Laboratory Medicine, Vol 32, Iss 3, Pp 229-236 (2024)
In this study, we aimed to analyze the correlations of high expressions of micro ribonucleic acids (miRNAs) with traditional proteins and prognosis of breast cancer.
Externí odkaz:
https://doaj.org/article/fcfa435a142c49de812367686a4bca86
Publikováno v:
In International Journal of Biological Macromolecules October 2024 278 Part 4
Publikováno v:
In Public Relations Review September 2024 50(3)
Autor:
Yan, Kun, Chen, Ding, Guo, Xiaoming, Wan, Yekai, Yang, Chenguang, Wang, Wenwen, Li, Xiufang, Lu, Zhentan, Wang, Dong
Publikováno v:
In Carbohydrate Polymers 15 December 2024 346
Autor:
Lu, Ying, Xu, Jiali, Liu, Yutong, Ban, Jingling, Li, Xiufang, Li, Mufang, Zhou, Yang, Wang, Dong, Piao, Longhai
Publikováno v:
In Composites Science and Technology 7 July 2024 253
Publikováno v:
In Computers & Industrial Engineering June 2024 192
Autor:
Sun, Qigong, Li, Xiufang, Shang, Fanhua, Liu, Hongying, Yang, Kang, Jiao, Licheng, Lin, Zhouchen
The training of deep neural networks (DNNs) always requires intensive resources for both computation and data storage. Thus, DNNs cannot be efficiently applied to mobile phones and embedded devices, which severely limits their applicability in indust
Externí odkaz:
http://arxiv.org/abs/2106.09886
Autor:
Wang, Shengjie, Xuan, Lina, Hu, Xiaolin, Sun, Feihan, Li, Siyun, Li, Xiufang, Yang, Hua, Guo, Jianjun, Duan, Xiaomeng, Luo, Huishan, Xin, Jieru, Chen, Jun, Hao, Junwei, Cui, Shijia, Liu, Dongping, Jiao, Lei, Zhang, Ying, Du, Zhimin, Sun, Lihua
Publikováno v:
In Canadian Journal of Cardiology April 2024 40(4):710-725
As an effective technique to achieve the implementation of deep neural networks in edge devices, model quantization has been successfully applied in many practical applications. No matter the methods of quantization aware training (QAT) or post-train
Externí odkaz:
http://arxiv.org/abs/2105.01353
Model quantization can reduce the model size and computational latency, it has become an essential technique for the deployment of deep neural networks on resourceconstrained hardware (e.g., mobile phones and embedded devices). The existing quantizat
Externí odkaz:
http://arxiv.org/abs/2103.05363