Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Phong, Nguyen Huu"'
Autor:
Phong, Nguyen Huu, Ribeiro, Bernardete
Recognizing human actions in video sequences, known as Human Action Recognition (HAR), is a challenging task in pattern recognition. While Convolutional Neural Networks (ConvNets) have shown remarkable success in image recognition, they are not alway
Externí odkaz:
http://arxiv.org/abs/2302.09187
Autor:
Phong, Nguyen Huu, Ribeiro, Bernardete
Publikováno v:
RECPAD 2017
In this research, we present our findings to recognize American Sign Language from series of hand gestures. While most researches in literature focus only on static handshapes, our work target dynamic hand gestures. Since dynamic signs dataset are ve
Externí odkaz:
http://arxiv.org/abs/2205.12261
Convolutional Neural Networks (ConvNets or CNNs) have been candidly deployed in the scope of computer vision and related fields. Nevertheless, the dynamics of training of these neural networks lie still elusive: it is hard and computationally expensi
Externí odkaz:
http://arxiv.org/abs/2205.10456
Autor:
Phong, Nguyen Huu, Ribeiro, Bernardete
Publikováno v:
IbPRIA 2019: Pattern Recognition and Image Analysis
Capsule Networks face a critical problem in computer vision in the sense that the image background can challenge its performance, although they learn very well on training data. In this work, we propose to improve Capsule Networks' architecture by re
Externí odkaz:
http://arxiv.org/abs/2007.15167
Autor:
Phong, Nguyen Huu, Ribeiro, Bernardete
Over the long history of machine learning, which dates back several decades, recurrent neural networks (RNNs) have been used mainly for sequential data and time series and generally with 1D information. Even in some rare studies on 2D images, these n
Externí odkaz:
http://arxiv.org/abs/2007.15161
Autor:
Phong, Nguyen Huu, Ribeiro, Bernardete
Publikováno v:
2017 4th Experiment@International Conference (exp.at'17)
Image recognition using Deep Learning has been evolved for decades though advances in the field through different settings is still a challenge. In this paper, we present our findings in searching for better image classifiers in offline and online en
Externí odkaz:
http://arxiv.org/abs/1903.07479
Autor:
Phong, Nguyen Huu, Ribeiro, Bernardete
Capsule Networks (CN) offer new architectures for Deep Learning (DL) community. Though its effectiveness has been demonstrated in MNIST and smallNORB datasets, the networks still face challenges in other datasets for images with distinct contexts. In
Externí odkaz:
http://arxiv.org/abs/1903.07497
Autor:
Son Pham Ngoc, Hanh Dang Ngoc, Thiem Do Dac, Son Vo Que, Ngoc Pham Thi Dan, Phong Nguyen Huu, Khuong Ho Van, Lien Hong Pham
Publikováno v:
Journal of Computer Science and Cybernetics. 36:205-231
This paper investigates a cognitive radio network where a secondary sender assists a primarytransmitter in relaying primary information to a primary receiver and also transmits its own information toa secondary recipient. This sender is capable of ja
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bae102e41e8cf3e73cb1fc9ad2911c0b
https://doi.org/10.15625/1813-9663/36/3/14987
https://doi.org/10.15625/1813-9663/36/3/14987
Publikováno v:
IET Communications. 13:1877-1885
This study investigates two-way relaying where an energy harvesting capable relay exchanges information between two sources. Legitimate information is wire-tapped by an eavesdropper. To intercept wire-tapping, this study exploits a friendly jammer. S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0c17d0ec1e9f10d66e7827d8f20ba38
https://doi.org/10.1049/iet-com.2018.6087
https://doi.org/10.1049/iet-com.2018.6087
Autor:
Son Vo-Que, Son Pham-Ngoc, Ngoc Pham-Thi-Dan, Phong Nguyen-Huu, Thiem Do-Dac, Lien Pham-Hong, Bao Ho-Quoc, Khuong Ho-Van
Publikováno v:
2020 International Conference on Advanced Technologies for Communications (ATC).
Energy scavenging overlay networks with artificial noise (ESONwAN) integrate three emerging (energy harvesting, cognitive radio, physical layer security) technologies to boost spectrum utilization efficiency, energy efficiency, and message security,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ad282f707d81ea2a23f69168d65b30c
https://doi.org/10.1109/atc50776.2020.9255480
https://doi.org/10.1109/atc50776.2020.9255480