Zobrazeno 1 - 10
of 438
pro vyhledávání: '"Zhang Mingxuan"'
Autor:
Dai Mingcong, Cai Jiahua, Ren Zejun, Zhang Mingxuan, Wang Jiaqi, Xiong Hongting, Ma Yihang, Wang Youwei, Zhou Sitong, Li Kuiju, Lv Zhentao, Wu Xiaojun
Publikováno v:
Nanophotonics, Vol 13, Iss 8, Pp 1493-1502 (2024)
Understanding the ultrafast excitation, detection, transportation, and manipulation of nanoscale spin dynamics in the terahertz (THz) frequency range is critical to developing spintronic THz optoelectronic nanodevices. However, the diffraction limita
Externí odkaz:
https://doaj.org/article/0aecf9b657194dd4bfa8277772e3522a
Large pretrained transformer models have revolutionized modern AI applications with their state-of-the-art performance in natural language processing (NLP). However, their substantial parameter count poses challenges for real-world deployment. To add
Externí odkaz:
http://arxiv.org/abs/2411.00969
Autor:
Yang, Zehao, Li, Jiahui, Liu, Shaojie, Ren, Zejun, Zhang, Mingxuan, Geng, Chunyan, Han, Xiufeng, Wan, Caihua, Wu, Xiaojun
Intense terahertz (THz) radiation in free space offers multifaceted capabilities for accelerating electron, understanding the mesoscale architecture in (bio)materials, elementary excitation and so on. Recently popularized spintronic THz emitters (STE
Externí odkaz:
http://arxiv.org/abs/2408.14054
Publikováno v:
E3S Web of Conferences, Vol 360, p 01090 (2022)
In recent years, the water supply task of urban water supply pipe network is more and more heavy, and leakage accidents of pipe network often occur, among which the most serious leakage accident is pipe burst accident. To solve this problem, this stu
Externí odkaz:
https://doaj.org/article/c95f341085904e0c877e808f63af3559
Sparse deep learning has become a popular technique for improving the performance of deep neural networks in areas such as uncertainty quantification, variable selection, and large-scale network compression. However, most existing research has focuse
Externí odkaz:
http://arxiv.org/abs/2310.03243
Publikováno v:
ICIP 2023
Pancreas segmentation is challenging due to the small proportion and highly changeable anatomical structure. It motivates us to propose a novel segmentation framework, namely Curriculum Knowledge Switching (CKS) framework, which decomposes detecting
Externí odkaz:
http://arxiv.org/abs/2306.12651
Learning on Graphs (LoG) is widely used in multi-client systems when each client has insufficient local data, and multiple clients have to share their raw data to learn a model of good quality. One scenario is to recommend items to clients with limit
Externí odkaz:
http://arxiv.org/abs/2212.12158
Autor:
Zhou, Tinglian, Li, Su, Zhu, Jiayan, Zeng, Guixiang, Lv, Zeen, Zhang, Mingxuan, Yao, Ke, Han, Haijie
Publikováno v:
In Journal of Controlled Release September 2024 373:306-318
Autor:
Liang, Wanle, Yan, Detian, Zhang, Mingxuan, Wang, Jikang, Ni, Dong, Yun, Suhe, Wei, Xiaosong, Zhang, Liwei, Fu, Haijiao
Publikováno v:
In Science of the Total Environment 10 December 2024 955
Publikováno v:
In Journal of Hazardous Materials 5 December 2024 480