Zobrazeno 1 - 10
of 228
pro vyhledávání: '"Lin, QingFeng"'
The key technologies of sixth generation (6G), such as ultra-massive multiple-input multiple-output (MIMO), enable intricate interactions between antennas and wireless propagation environments. As a result, it becomes necessary to develop joint model
Externí odkaz:
http://arxiv.org/abs/2412.06178
Autor:
Kou, Wei-Bin, Lin, Qingfeng, Tang, Ming, Ye, Rongguang, Wang, Shuai, Zhu, Guangxu, Wu, Yik-Chung
Street Scene Semantic Understanding (denoted as TriSU) is a complex task for autonomous driving (AD). However, inference model trained from data in a particular geographical region faces poor generalization when applied in other regions due to inter-
Externí odkaz:
http://arxiv.org/abs/2409.19560
Autor:
Kou, Wei-Bin, Zhu, Guangxu, Ye, Rongguang, Lin, Qingfeng, Ren, Zeyi, Tang, Ming, Wu, Yik-Chung
Various adverse weather conditions pose a significant challenge to autonomous driving (AD) street scene semantic understanding (segmentation). A common strategy is to minimize the disparity between images captured in clear and adverse weather conditi
Externí odkaz:
http://arxiv.org/abs/2409.14737
The movable antenna (MA) is a promising technology to exploit more spatial degrees of freedom for enhancing wireless system performance. However, the MA-aided system introduces the non-convex antenna distance constraints, which poses challenges in th
Externí odkaz:
http://arxiv.org/abs/2407.08230
Street Scene Semantic Understanding (denoted as TriSU) is a crucial but complex task for world-wide distributed autonomous driving (AD) vehicles (e.g., Tesla). Its inference model faces poor generalization issue due to inter-city domain-shift. Hierar
Externí odkaz:
http://arxiv.org/abs/2407.01103
Autor:
Kou, Wei-Bin, Lin, Qingfeng, Tang, Ming, Xu, Sheng, Ye, Rongguang, Leng, Yang, Wang, Shuai, Li, Guofa, Chen, Zhenyu, Zhu, Guangxu, Wu, Yik-Chung
Deep learning-based Autonomous Driving (AD) models often exhibit poor generalization due to data heterogeneity in an ever domain-shifting environment. While Federated Learning (FL) could improve the generalization of an AD model (known as FedAD syste
Externí odkaz:
http://arxiv.org/abs/2405.04146
Activity detection is an important task in the next generation grant-free multiple access. While there are a number of existing algorithms designed for this purpose, they mostly require precise information about the network, such as large-scale fadin
Externí odkaz:
http://arxiv.org/abs/2401.16775
Device activity detection in the emerging cell-free massive multiple-input multiple-output (MIMO) systems has been recognized as a crucial task in machine-type communications, in which multiple access points (APs) jointly identify the active devices
Externí odkaz:
http://arxiv.org/abs/2210.00451
Autor:
Li, Zongze, Wang, Shuai, Lin, Qingfeng, Li, Yang, Wen, Miaowen, Wu, Yik-Chung, Poor, H. Vincent
Reconfigurable intelligent surfaces (RISs) have a revolutionary capability to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting elements must b
Externí odkaz:
http://arxiv.org/abs/2204.13372
Autor:
He, Shuyan, Xiao, Xinru, Ma, Chenglong, Liu, Ye, Lin, Qingfeng, Qian, Wenjun, Cao, Cheng, Ren, Shujuan, Chen, Jie, Mi, Yedong, Shen, Dong
Publikováno v:
In Experimental Cell Research 1 May 2024 438(1)
