Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Luong Trung Nguyen"'
Publikováno v:
IEEE Access, Vol 10, Pp 19401-19411 (2022)
Weakly-supervised semantic segmentation (WSSS) aims to train a semantic segmentation network using weak labels. Recent approaches generate the pseudo-label from the image-level label and then exploit it as a pixel-level supervision in the segmentatio
Externí odkaz:
https://doaj.org/article/e36c367ead334851adca837559fec336
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2019, Iss 1, Pp 1-9 (2019)
Abstract Frequency estimation of a tonal signal in passive sonar systems is crucial to the identification of the marine object. In the conventional techniques, a basis mismatch error caused by the discretization of the frequency domain is unavoidable
Externí odkaz:
https://doaj.org/article/5e2857f61f574f0fa6aa6c1a76840c43
Publikováno v:
IEEE Access, Vol 7, Pp 94215-94237 (2019)
As a paradigm to recover unknown entries of a matrix from partial observations, low-rank matrix completion (LRMC) has generated a great deal of interest. Over the years, there have been lots of works on this topic, but it might not be easy to grasp t
Externí odkaz:
https://doaj.org/article/9f8fee96dbfa483e97305960bbabb4c3
Publikováno v:
IEEE Wireless Communications Letters. 10:2115-2119
In this letter, we propose a deep learning-based technique to recover a Euclidean distance matrix D in IoT network localization. In contrast to conventional localization algorithms that search D over a whole set of matrices, the proposed technique, c
Publikováno v:
IEEE Transactions on Signal Processing. 69:6299-6313
Federated averaging (FedAvg) is a popular federated learning (FL) technique that updates the global model by averaging local models and then transmits the updated global model to devices for their local model update. One main limitation of FedAvg is
Publikováno v:
IEEE Transactions on Information Theory. 66:5072-5096
In this paper, we put forth a new joint sparse recovery algorithm called signal space matching pursuit (SSMP). The key idea of the proposed SSMP algorithm is to sequentially investigate the support of jointly sparse vectors to minimize the subspace d
Akademický článek
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Publikováno v:
2021 55th Asilomar Conference on Signals, Systems, and Computers.
Autor:
Byonghyo Shim, Luong Trung Nguyen
Publikováno v:
ICASSP
Federated learning is a machine learning framework that enables AI models training over a network of multiple user devices without revealing user data stored in the devices. Popularly used federated learning technique to enhance the learning performa
Publikováno v:
IEEE Transactions on Communications. 67:5833-5847
Location awareness, providing the ability to identify the location of sensor, machine, vehicle, and wearable device, is a rapidly growing trend of hyper-connected society and one of the key ingredients for the Internet of Things (IoT) era. In order t