Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Zhuqing Yuan"'
Autor:
Bin Xu, Lizhou Liu, Zhaotian Yan, Zhuqing Yuan, Lu Zhang, Wei Zhou, Ruikun Mai, Zhengyou He, Yongpan Liu, Huazhong Yang
Publikováno v:
IEEE Transactions on Industrial Electronics. 70:6984-6992
Autor:
Jingyu Wang, Songming Yu, Zhuqing Yuan, Jinshan Yue, Zhe Yuan, Ruoyang Liu, Yanzhi Wang, Huazhong Yang, Xueqing Li, Yongpan Liu
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41:5043-5056
Autor:
Wenyu Sun, Yixiong Yang, Yue Jinshan, Zhe Yuan, Yongpan Liu, Ruoyang Liu, Jingyu Wang, Zhuqing Yuan, Huazhong Yang, Xiaoyu Feng, Xueqing Li
Publikováno v:
IEEE Journal of Solid-State Circuits. 57:2574-2585
An energy-efficient convolutional neural network (CNN) accelerator is proposed for the video application. Previous works exploited the sparsity of differential (Diff) frame activation, but the improvement is limited as many Diff-frame data is small b
Publikováno v:
Applied Sciences, Vol 10, Iss 11, p 4023 (2020)
An end-to-end image compression framework based on deep residual learning is proposed. Three levels of residual learning are adopted to improve the compression quality: (1) the ResNet structure; (2) the deep channel residual learning for quantization
Externí odkaz:
https://doaj.org/article/afb10130e63047ae9707e9d12eee31e5
Publikováno v:
2022 IEEE International Symposium on Circuits and Systems (ISCAS).
Publikováno v:
Minerva Surgery; Feb2023, Vol. 78 Issue 1, p114-116, 3p
Publikováno v:
Minerva surgery.
Autor:
Songming Yu, Lu Zhang, Jingyu Wang, Jinshan Yue, Zhuqing Yuan, Xueqing Li, Huazhong Yang, Yongpan Liu
Publikováno v:
2021 IEEE 10th Non-Volatile Memory Systems and Applications Symposium (NVMSA).
Publikováno v:
Renewable and Sustainable Energy Reviews. 155:111942
Carbon reduction actions may cause regions that recently entered the middle-income threshold to fall into “ecological poverty”. Identifying the factors driving industrial carbon emission costs (ICECs) growth is difficult and important for achievi
Publikováno v:
A-SSCC
This paper proposes an algorithm and hardware co-design methodology to accelerate CNNs for pix2pix tasks. An importance map is introduced to train an activation-sparse CNN model, which can effectively reduce the computing cost and external data trans