Zobrazeno 1 - 10
of 222
pro vyhledávání: '"Chunbo Luo"'
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:
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
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:
IEEE Transactions on Big Data. :1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14e500ebd68059717bdd00469656a32b
https://doi.org/10.1109/tbdata.2023.3278988
https://doi.org/10.1109/tbdata.2023.3278988
An Autoencoder-based I/Q Channel Interaction Enhancement Method for Automatic Modulation Recognition
Publikováno v:
IEEE Transactions on Vehicular Technology. :1-6
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1f1791fd0934dd9b1c810086e00e01c
https://doi.org/10.1109/tvt.2023.3248625
https://doi.org/10.1109/tvt.2023.3248625
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-15
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::379f8d6a7494cc1105e25f59d7ac04a5
https://doi.org/10.1109/tgrs.2023.3265650
https://doi.org/10.1109/tgrs.2023.3265650
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