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pro vyhledávání: '"Liu, Yuxiang"'
In response to the demand for real-time performance and control quality in industrial Internet of Things (IoT) environments, this paper proposes an optimization control system based on deep reinforcement learning and edge computing. The system levera
Externí odkaz:
http://arxiv.org/abs/2403.07923
Dark photons, aside from constituting non-relativistic dark matter, can also be generated relativistically through the decay or annihilation of other dark matter candidates, contributing to a galactic dark photon background. The production of dark ph
Externí odkaz:
http://arxiv.org/abs/2402.03432
A Schubert class is called {\em rigid} if it can only be represented by Schubert varieties. The rigid Schubert classes have been classified in Grassmannians \cite{Coskun2011RigidAN} and orthogonal Grassmannians \cite{arXiv:2210.14540}. In this paper,
Externí odkaz:
http://arxiv.org/abs/2401.11375
Autor:
Bozhidarova, Malvina, Chang, Jonathn, Ale-rasool, Aaishah, Liu, Yuxiang, Ma, Chongyao, Bertozzi, Andrea L., Brantingham, P. Jeffrey, Lin, Junyuan, Krishnagopal, Sanjukta
This study explores the dynamic relationship between online discourse, as observed in tweets, and physical hate crimes, focusing on marginalized groups. Leveraging natural language processing techniques, including keyword extraction and topic modelin
Externí odkaz:
http://arxiv.org/abs/2311.11163
We introduce a new task called *entity-centric question generation* (ECQG), motivated by real-world applications such as topic-specific learning, assisted reading, and fact-checking. The task aims to generate questions from an entity perspective. To
Externí odkaz:
http://arxiv.org/abs/2310.14126
Real-time measurement of relative humidity (RH) is important to many physical, chemical, and biological processes. However, in processes that involve harsh conditions such as high temperatures, strong electromagnetic interferences, and complex spatia
Externí odkaz:
http://arxiv.org/abs/2307.04818
Despite the significant progress in 6-DoF visual localization, researchers are mostly driven by ground-level benchmarks. Compared with aerial oblique photography, ground-level map collection lacks scalability and complete coverage. In this work, we p
Externí odkaz:
http://arxiv.org/abs/2302.06287
Autor:
Ge, Jidong, Liu, Yuxiang, Gui, Jie, Fang, Lanting, Lin, Ming, Kwok, James Tin-Yau, Huang, LiGuo, Luo, Bin
Self-supervised learning enables networks to learn discriminative features from massive data itself. Most state-of-the-art methods maximize the similarity between two augmentations of one image based on contrastive learning. By utilizing the consiste
Externí odkaz:
http://arxiv.org/abs/2301.03041
With the rapid development of smart manufacturing, edge computing-oriented microservice platforms are emerging as an important part of production control. In the containerized deployment of microservices, layer sharing can reduce the huge bandwidth c
Externí odkaz:
http://arxiv.org/abs/2212.14183
Dose verification based on proton-induced positron emitters is a promising quality assurance tool and may leverage the strength of artificial intelligence. To move a step closer towards practical application, the sensitivity analysis of two factors n
Externí odkaz:
http://arxiv.org/abs/2212.11352