Zobrazeno 1 - 10
of 1 483
pro vyhledávání: '"Tran, Vu A."'
Fairness in artificial intelligence and machine learning (AI/ML) models is becoming critically important, especially as decisions made by these systems impact diverse groups. In education, a vital sector for all countries, the widespread application
Externí odkaz:
http://arxiv.org/abs/2410.06423
Autor:
Khanh, Tran Vu, Raich, Andrew
We establish general sufficient conditions for exact (and global) regularity in the $\bar\partial$-Neumann problem on $(p,q)$-forms, $0 \leq p \leq n$ and $1\leq q \leq n$, on a pseudoconvex domain $\Omega$ with smooth boundary $b\Omega$ in an $n$-di
Externí odkaz:
http://arxiv.org/abs/2408.04512
Autor:
Tran, Vu Phi, Perera, Asanka G., Garratt, Matthew A., Kasmarik, Kathryn, Anavatti, Sreenatha G.
This paper introduces a state-machine model for a multi-modal, multi-robot environmental sensing algorithm tailored to dynamic real-world settings. The algorithm uniquely combines two exploration strategies for gas source localization and mapping: (1
Externí odkaz:
http://arxiv.org/abs/2407.01308
Publikováno v:
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 3752-3756
This paper addresses the challenges of an early flood warning caused by complex convective systems (CSs), by using Low-Earth Orbit and Geostationary satellite data. We focus on a sequence of extreme events that took place in central Vietnam during Oc
Externí odkaz:
http://arxiv.org/abs/2403.14395
Ship detection from satellite imagery using Deep Learning (DL) is an indispensable solution for maritime surveillance. However, applying DL models trained on one dataset to others having differences in spatial resolution and radiometric features requ
Externí odkaz:
http://arxiv.org/abs/2403.13698
Autor:
Tran, Vu, Nguyen, Ha-Thanh, Vo, Trung, Luu, Son T., Dang, Hoang-Anh, Le, Ngoc-Cam, Le, Thi-Thuy, Nguyen, Minh-Tien, Nguyen, Truong-Son, Nguyen, Le-Minh
In this new era of rapid AI development, especially in language processing, the demand for AI in the legal domain is increasingly critical. In the context where research in other languages such as English, Japanese, and Chinese has been well-establis
Externí odkaz:
http://arxiv.org/abs/2403.03435
Radio source localization can benefit many fields, including wireless communications, radar, radio astronomy, wireless sensor networks, positioning systems, and surveillance systems. However, accurately estimating the position of a radio transmitter
Externí odkaz:
http://arxiv.org/abs/2312.03493
We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep neural networks. On the other hand, we exp
Externí odkaz:
http://arxiv.org/abs/2309.08187
This paper proposes a state-machine model for a multi-modal, multi-robot environmental sensing algorithm. This multi-modal algorithm integrates two different exploration algorithms: (1) coverage path planning using variable formations and (2) collabo
Externí odkaz:
http://arxiv.org/abs/2306.04083
Autor:
Astri Nur Faizah, Daisuke Kobayashi, Faustus Akankperiwen Azerigyik, Ryo Matsumura, Izumi Kai, Yoshihide Maekawa, Yukiko Higa, Kentaro Itokawa, Toshinori Sasaki, Kris Cahyo Mulyatno, Sri Subekti, Maria Inge Lusida, Etik Ainun Rohmah, Yasuko Mori, Yusuf Ozbel, Chizu Sanjoba, Tran vu Phong, Tran Cong Tu, Shinji Kasai, Kyoko Sawabe, Haruhiko Isawa
Publikováno v:
Emerging Microbes and Infections (2024)
Japanese encephalitis virus (JEV) genotype IV (GIV) is one of the least common and most neglected genotypes worldwide, having been identified only on a few Indonesian islands until it was recently found to be the cause of outbreaks that occurred in s
Externí odkaz:
https://doaj.org/article/36226f2b95654812a1d02be61e492590
