Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Hien Van Nguyen"'
Autor:
Syed Rizvi, Akash Awasthi, Maria J. Peláez, Zhihui Wang, Vittorio Cristini, Hien Van Nguyen, Prashant Dogra
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The COVID-19 pandemic affected countries across the globe, demanding drastic public health policies to mitigate the spread of infection, which led to economic crises as a collateral damage. In this work, we investigate the impact of human mo
Externí odkaz:
https://doaj.org/article/009bd38ba2254202b824c999819099e4
Publikováno v:
Nigerian Postgraduate Medical Journal, Vol 31, Iss 2, Pp 170-172 (2024)
Pelvic organ prolapse refers to the descent of pelvic floor organs resulting from the weakening of pelvic muscles, fascia and connective tissue. The overall prevalence of pelvic organ prolapse is approximately 41%, including bladder prolapse (25%–3
Externí odkaz:
https://doaj.org/article/cb90e747000d44b0a976bbd1e6b7dbbe
Autor:
Samira Zare, Hien Van Nguyen
Publikováno v:
IEEE Access, Vol 11, Pp 137758-137768 (2023)
Despite the remarkable progress of self-supervised learning (SSL), how self-supervised representations generalize to out-of-distribution data remains little understood. In this paper, we study the effects of distribution shifts on self-supervised rep
Externí odkaz:
https://doaj.org/article/6b27170ff1c04674bdb2193eb287587c
Autor:
Samira Zare, Hien Van Nguyen
Publikováno v:
Computer Sciences & Mathematics Forum, Vol 9, Iss 1, p 2 (2024)
Standard training via empirical risk minimization may result in making predictions that overly rely on spurious correlations. This can degrade the generalization to out-of-distribution settings where these correlations no longer hold. Invariant learn
Externí odkaz:
https://doaj.org/article/e3305bd69e9646b3b2c7c7a666e434cd
Autor:
Dragan Maric, Jahandar Jahanipour, Xiaoyang Rebecca Li, Aditi Singh, Aryan Mobiny, Hien Van Nguyen, Andrea Sedlock, Kedar Grama, Badrinath Roysam
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
It is challenging to map complex processes in brain tissue. Here the authors report a toolkit enabling large-scale multiplexed IHC and automated cell classification whereby they use a conventional epifluorescence microscope and deep neural networks t
Externí odkaz:
https://doaj.org/article/141fd0786f3a48a8b0d559b8d4a15b41
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract Deep neural networks (DNNs) have achieved state-of-the-art performance in many important domains, including medical diagnosis, security, and autonomous driving. In domains where safety is highly critical, an erroneous decision can result in
Externí odkaz:
https://doaj.org/article/ff6a04b4a5f649c98b73aae38d3ec8c3
Publikováno v:
IEEE Access, Vol 8, Pp 102477-102492 (2020)
The development of Long Term Evolution (LTE) enables wireless communication with high transmission rate, low latency, and wide coverage area. These outstanding features of LTE support the next generation of vehicle-to-everything (V2X) communication,
Externí odkaz:
https://doaj.org/article/ea92d8e67ae64e64996b274763f2fffc
Autor:
Pengyu Yuan, Shirui Wang, Wenyi Hu, Prashanth Nadukandi, German Ocampo Botero, Xuqing Wu, Hien Van Nguyen, Jiefu Chen
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-19
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef591c11f1ddce0ace3016ab43a7e1f3
https://doi.org/10.1109/tgrs.2022.3167546
https://doi.org/10.1109/tgrs.2022.3167546
