Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Chunbo Luo"'
Publikováno v:
Frontiers in Marine Science, Vol 11 (2024)
Externí odkaz:
https://doaj.org/article/dc73a674826c4949a810e25c4079617f
Publikováno v:
EURASIP Journal on Wireless Communications and Networking, Vol 2020, Iss 1, Pp 1-20 (2020)
Abstract Cooperative aerial wireless networks composed of small unmanned aerial vehicles(UAVs) are easy and fast to deploy and provide on the fly communication facilities in situations where part of the communication infrastructure is destroyed and t
Externí odkaz:
https://doaj.org/article/0072210eba3e4c458545739ef2b416a6
Logit knowledge distillation attracts increasing attention due to its practicality in recent studies. However, it often suffers inferior performance compared to the feature knowledge distillation. In this paper, we argue that existing logit-based met
Externí odkaz:
http://arxiv.org/abs/2403.13512
Publikováno v:
Mathematics, Vol 10, Iss 8, p 1320 (2022)
Graph representation learning is a significant challenge in graph signal processing (GSP). The flourishing development of graph neural networks (GNNs) provides effective representations for GSP. To effectively learn from graph signals, we propose a r
Externí odkaz:
https://doaj.org/article/04b45bcab7e34ddfb2def585ff670bd7
Autor:
Emmanuel Osei-Mensah, Saqr Khalil Saeed Thabet, Chunbo Luo, Emelia Asiedu-Ayeh, Olusola Bamisile, Isaac Osei Nyantakyi, Humphrey Adun
Publikováno v:
Applied Sciences, Vol 12, Iss 9, p 4205 (2022)
Online video is anticipated to be the largest fraction of all mobile network traffic aside from the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented challenges to the current network architecture. Edge c
Externí odkaz:
https://doaj.org/article/87cd7d3bd1f34a27a4e9e21f7f507e71
Publikováno v:
Water, Vol 13, Iss 24, p 3520 (2021)
Urban flooding is a devastating natural hazard for cities around the world. Flood risk mapping is a key tool in flood management. However, it is computationally expensive to produce flood risk maps using hydrodynamic models. To this end, this paper i
Externí odkaz:
https://doaj.org/article/986892551e1f428b826fed8d6852b906
Publikováno v:
Entropy, Vol 23, Iss 12, p 1678 (2021)
With the proliferation of Unmanned Aerial Vehicles (UAVs) to provide diverse critical services, such as surveillance, disaster management, and medicine delivery, the accurate detection of these small devices and the efficient classification of their
Externí odkaz:
https://doaj.org/article/38d847cb717b41178e4f10fd4c057e5b
Publikováno v:
Remote Sensing, Vol 13, Iss 15, p 3053 (2021)
Remote sensing change detection (RSCD) is an important yet challenging task in Earth observation. The booming development of convolutional neural networks (CNNs) in computer vision raises new possibilities for RSCD, and many recent RSCD methods have
Externí odkaz:
https://doaj.org/article/c219dd84ba1749079effee21a670b607
Publikováno v:
GIScience & Remote Sensing, Vol 54, Iss 5, Pp 741-758 (2017)
The recent emergence of deep learning for characterizing complex patterns in remote sensing imagery reveals its high potential to address some classic challenges in this domain, e.g. scene classification. Typical deep learning models require extremel
Externí odkaz:
https://doaj.org/article/0a658e8550ee4453883c1143be681c71
Autor:
Tianxiao Zhao, Chunbo Luo, Jianming Zhou, Dechun Guo, Ning Chen, Pablo Casaseca-de-la-Higuera
Publikováno v:
Applied Sciences, Vol 10, Iss 13, p 4420 (2020)
In supporting communications with unmanned aerial vehicles (UAVs) as aerial user equipments (aUEs) in cellular systems, the current beamforming schemes based on channel state estimation are facing severe challenges from the pilot contamination effect
Externí odkaz:
https://doaj.org/article/bd091becafd04999bfff49ac060887bf