Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Kevin S Chan"'
Autor:
Janet Bouttell, Jeremy Teoh, Peter K Chiu, Kevin S Chan, Chi-Fai Ng, Robert Heggie, Neil Hawkins
Publikováno v:
PLoS ONE, Vol 14, Iss 4, p e0215279 (2019)
A recent study showed that the Prostate Health Index may avoid unnecessary biopsies in men with prostate specific antigen 4-10ng/ml and normal digital rectal examination in the diagnosis of prostate cancer in Hong Kong. This study aimed to conduct an
Externí odkaz:
https://doaj.org/article/42aafabfd3a44d75841208a32c3eb3d6
Autor:
Pradipta Ghosh, Marcos A. M. Vieira, Gunjan Verma, Jonathan Bunton, Ramesh Govindan, Kevin S. Chan, Paulo Tabuada, Dimitrios Pylorof, Gaurav S. Sukhatme
Publikováno v:
IEEE Transactions on Mobile Computing. 22:1810-1824
While most networks have long lifetimes, temporary network infrastructure is often useful for special events, pop-up retail, or disaster response. An instant IoT network is one that is rapidly constructed, used for a few days, then dismantled. We con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41bf42a1e281c7e61144b35be24eec97
https://doi.org/10.1109/tmc.2021.3099005
https://doi.org/10.1109/tmc.2021.3099005
Publikováno v:
Complex Networks and Their Applications XI ISBN: 9783031211263
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cbf50809d01238ca7196b4dd3c241a0
https://doi.org/10.1007/978-3-031-21127-0_9
https://doi.org/10.1007/978-3-031-21127-0_9
Autor:
Thomas F. La Porta, Fidan Mehmeti, Zongqing Lu, Kevin S. Chan, Noor Felemban, Swati Rallapalli, Hana Khamfroush
Publikováno v:
IEEE Transactions on Mobile Computing. 20:1574-1589
Mobile devices collect a large amount of visual data that are useful for many applications. Searching for an object of interest over a network of mobile devices can aid human analysts in a variety of situations. However, processing the information on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e39970d41b22b7ffc74f3ad96e25d650
https://doi.org/10.1109/tmc.2019.2963150
https://doi.org/10.1109/tmc.2019.2963150
Autor:
Konstantinos Poularakis, Thomas F. La Porta, Fidan Mehmeti, Ting He, Hana Khamfroush, Shiqiang Wang, Vajiheh Farhadi, Kevin S. Chan
Publikováno v:
IEEE/ACM Transactions on Networking. 29:779-792
Mobile edge computing provides the opportunity for wireless users to exploit the power of cloud computing without a large communication delay. To serve data-intensive applications (e.g., video analytics, machine learning tasks) from the edge, we need
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a53fdfd92b884c2d598590ad3822b94
https://doi.org/10.1109/tnet.2020.3048613
https://doi.org/10.1109/tnet.2020.3048613
Publikováno v:
IEEE Transactions on Mobile Computing. 20:352-365
Convolutional Neural Networks (ConvNets/CNNs) have revolutionized the research in computer vision, due to their ability to capture complex patterns, resulting in high inference accuracies. However, the increasingly complex nature of these neural netw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf7652fd9a03c1a402d7a3574fe8bd8b
https://doi.org/10.1109/tmc.2019.2946538
https://doi.org/10.1109/tmc.2019.2946538
Publikováno v:
INFOCOM
The rapid development of network function virtualization (NFV) enables a communication network to provide in-network services using virtual network functions (VNFs) deployed on general IT hardware. While existing studies on NFV focused on how to prov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b4132f806e00d2ea0416e9ddc8af594
https://doi.org/10.1109/tnet.2020.2985908
https://doi.org/10.1109/tnet.2020.2985908
Publikováno v:
IEEE Control Systems Letters. 4:283-288
In this letter, we consider the problem of designing robust observers for uncertain polynomial systems. The results are applicable to polynomial systems with dynamics that are affine in the control and disturbance variables, and a perturbed linear ou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36ba2125b0b0c465ccc397e924f36481
https://doi.org/10.1109/lcsys.2019.2925511
https://doi.org/10.1109/lcsys.2019.2925511
Publikováno v:
IEEE/ACM Transactions on Networking. 28:196-209
The vast adoption of mobile devices with cameras has greatly contributed to the proliferation of the creation and distribution of videos. For a variety of purposes, valuable information may be extracted from these videos. While the computational capa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b8834ab2bb877868859c73d748eb8a2
https://doi.org/10.1109/tnet.2019.2954909
https://doi.org/10.1109/tnet.2019.2954909
Federated learning (FL) is a useful tool in distributed machine learning that utilizes users' local datasets in a privacy-preserving manner. When deploying FL in a constrained wireless environment; however, training models in a time-efficient manner
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7aa1b001fd9ea814ae960c3244d9bd80