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of 80 701
pro vyhledávání: '"Gee BE"'
Millimeter-wave radar is promising to provide robust and accurate vital sign monitoring in an unobtrusive manner. However, the radar signal might be distorted in propagation by ambient noise or random body movement, ruining the subtle cardiac activit
Externí odkaz:
http://arxiv.org/abs/2410.08656
Autor:
Yao, Michael S., Chae, Allison, Kahn Jr., Charles E., Witschey, Walter R., Gee, James C., Sagreiya, Hersh, Bastani, Osbert
Diagnostic imaging studies are an increasingly important component of the workup and management of acutely presenting patients. However, ordering appropriate imaging studies according to evidence-based medical guidelines is a challenging task with a
Externí odkaz:
http://arxiv.org/abs/2409.19177
Autor:
Meng, Mark Huasong, Yan, Chuan, Hao, Yun, Zhang, Qing, Wang, Zeyu, Wang, Kailong, Teo, Sin Gee, Bai, Guangdong, Dong, Jin Song
Third-party Software Development Kits (SDKs) are widely adopted in Android app development, to effortlessly accelerate development pipelines and enhance app functionality. However, this convenience raises substantial concerns about unauthorized acces
Externí odkaz:
http://arxiv.org/abs/2409.10411
Autor:
Guan, Runwei, Liu, Jianan, Jia, Liye, Zhao, Haocheng, Yao, Shanliang, Zhu, Xiaohui, Man, Ka Lok, Lim, Eng Gee, Smith, Jeremy, Yue, Yutao
Recently, visual grounding and multi-sensors setting have been incorporated into perception system for terrestrial autonomous driving systems and Unmanned Surface Vehicles (USVs), yet the high complexity of modern learning-based visual grounding mode
Externí odkaz:
http://arxiv.org/abs/2408.17207
Autor:
Cutler, Elizabeth, Xing, Yuning, Cui, Tony, Zhou, Brendan, van Rijnsoever, Koen, Hart, Ben, Valencia, David, Ong, Lee Violet C., Gee, Trevor, Liarokapis, Minas, Williams, Henry
Publikováno v:
Australasian conference on robotics and automation (ACRA 2023)
Reinforcement Learning (RL) training is predominantly conducted in cost-effective and controlled simulation environments. However, the transfer of these trained models to real-world tasks often presents unavoidable challenges. This research explores
Externí odkaz:
http://arxiv.org/abs/2408.14747
Autor:
Lau, Gee-Choon, Shiu, Wai Chee
For a graph $G(V,E)$ of size $q$, a bijection $f : E(G) \to [1,q]$ is a local antimagc labeling if it induces a vertex labeling $f^+ : V(G) \to \mathbb{N}$ such that $f^+(u) \ne f^+(v)$, where $f^+(u)$ is the sum of all the incident edge label(s) of
Externí odkaz:
http://arxiv.org/abs/2408.06703
Classical optimization and learning-based methods are the two reigning paradigms in deformable image registration. While optimization-based methods boast generalizability across modalities and robust performance, learning-based methods promise peak p
Externí odkaz:
http://arxiv.org/abs/2408.05839
Autor:
Lau, Gee-Choon, Shiu, Wai Chee
It is known that null graphs and 1-regular graphs are the only regular graphs without local antimagic chromatic number. In this paper, we use matrices of size $(2m+1) \times (2k+1)$ to completely determine the local antimagic chromatic number of the
Externí odkaz:
http://arxiv.org/abs/2408.04942
Radar-based contactless cardiac monitoring has become a popular research direction recently, but the fine-grained electrocardiogram (ECG) signal is still hard to reconstruct from millimeter-wave radar signal. The key obstacle is to decouple the cardi
Externí odkaz:
http://arxiv.org/abs/2408.01672
Autor:
Gee, Marissa, Vladimirsky, Alexander
Piecewise-deterministic Markov processes (PDMPs) are often used to model abrupt changes in the global environment or capabilities of a controlled system. This is typically done by considering a set of "operating modes" (each with its own system dynam
Externí odkaz:
http://arxiv.org/abs/2408.01335