Zobrazeno 1 - 10
of 319
pro vyhledávání: '"Wu, Dapeng Oliver"'
This paper is concerned with unmanned aerial vehicle (UAV) video coding and transmission in scenarios such as emergency rescue and environmental monitoring. Unlike existing methods of modeling UAV video source coding and channel transmission separate
Externí odkaz:
http://arxiv.org/abs/2408.06667
Autor:
Chen, Xingyan, Du, Tian, Wang, Mu, Gu, Tiancheng, Zhao, Yu, Kou, Gang, Xu, Changqiao, Wu, Dapeng Oliver
Federated learning, as a promising distributed learning paradigm, enables collaborative training of a global model across multiple network edge clients without the need for central data collecting. However, the heterogeneity of edge data distribution
Externí odkaz:
http://arxiv.org/abs/2403.02360
Mobile Edge Computing (MEC) is a new computing paradigm that enables cloud computing and information technology (IT) services to be delivered at the network's edge. By shifting the load of cloud computing to individual local servers, MEC helps meet t
Externí odkaz:
http://arxiv.org/abs/2401.01589
This paper is concerned with the issue of improving video subscribers' quality of experience (QoE) by deploying a multi-unmanned aerial vehicle (UAV) network. Different from existing works, we characterize subscribers' QoE by video bitrates, latency,
Externí odkaz:
http://arxiv.org/abs/2307.12264
This paper addresses the problem of cross-modal object tracking from RGB videos and event data. Rather than constructing a complex cross-modal fusion network, we explore the great potential of a pre-trained vision Transformer (ViT). Particularly, we
Externí odkaz:
http://arxiv.org/abs/2307.04129
Autor:
Zhang, Tianci, Chen, Shutong, Chen, Zhengchuan, Tian, Zhong, Jia, Yunjian, Wang, Min, Wu, Dapeng Oliver
Lots of real-time applications over Internet of things (IoT)-based status update systems have imperative demands on information freshness, which is usually evaluated by age of information (AoI). Compared to the average AoI and peak AoI (PAoI), violat
Externí odkaz:
http://arxiv.org/abs/2210.16172
Internet of unmanned aerial vehicle (I-UAV) networks promise to accomplish sensing and transmission tasks quickly, robustly, and cost-efficiently via effective cooperation among UAVs. To achieve the promising benefits, the crucial I-UAV networking is
Externí odkaz:
http://arxiv.org/abs/2111.07078
In this paper, we propose a single-agent Monte Carlo based reinforced feature selection (MCRFS) method, as well as two efficiency improvement strategies, i.e., early stopping (ES) strategy and reward-level interactive (RI) strategy. Feature selection
Externí odkaz:
http://arxiv.org/abs/2109.14180
Autor:
Giovanini, Luiz, Ceschin, Fabrício, Silva, Mirela, Chen, Aokun, Kulkarni, Ramchandra, Banda, Sanjay, Lysaght, Madison, Qiao, Heng, Sapountzis, Nikolaos, Sun, Ruimin, Matthews, Brandon, Wu, Dapeng Oliver, Grégio, André, Oliveira, Daniela
This paper investigates whether computer usage profiles comprised of process-, network-, mouse-, and keystroke-related events are unique and consistent over time in a naturalistic setting, discussing challenges and opportunities of using such profile
Externí odkaz:
http://arxiv.org/abs/2105.09900
Publikováno v:
IEEE Transactions on Artificial Intelligence 2020
Real data often appear in the form of multiple incomplete views. Incomplete multi-view clustering is an effective method to integrate these incomplete views. Previous methods only learn the consistent information between different views and ignore th
Externí odkaz:
http://arxiv.org/abs/2011.11194