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pro vyhledávání: '"Cho, Jin"'
Autor:
Yin, Shenwei, Cho, Jin-Woo, Feng, Demeng, Mei, Hongyan, Kumar, Tanuj, Wan, Chenghao, Jin, Yeonghoon, Kim, Minjeong, Kats, Mikhail A.
The dispersive linear optical properties of materials are frequently described using oscillator models, where the oscillators represent interactions between light and various material resonances (vibrational, free-carrier, interband, etc.). The state
Externí odkaz:
http://arxiv.org/abs/2409.05323
Cybergrooming emerges as a growing threat to adolescent safety and mental health. One way to combat cybergrooming is to leverage predictive artificial intelligence (AI) to detect predatory behaviors in social media. However, these methods can encount
Externí odkaz:
http://arxiv.org/abs/2405.13154
Competitive Influence Maximization (CIM) involves entities competing to maximize influence in online social networks (OSNs). Current Deep Reinforcement Learning (DRL) methods in CIM rely on simplistic binary opinion models (i.e., an opinion is repres
Externí odkaz:
http://arxiv.org/abs/2404.18826
Autor:
Li, Changbin, Li, Kangshuo, Ou, Yuzhe, Kaplan, Lance M., Jøsang, Audun, Cho, Jin-Hee, Jeong, Dong Hyun, Chen, Feng
Deep neural networks (DNNs) have been shown to perform well on exclusive, multi-class classification tasks. However, when different classes have similar visual features, it becomes challenging for human annotators to differentiate them. This scenario
Externí odkaz:
http://arxiv.org/abs/2404.10980
We propose a novel energy-aware federated learning (FL)-based system, namely SusFL, for sustainable smart farming to address the challenge of inconsistent health monitoring due to fluctuating energy levels of solar sensors. This system equips animals
Externí odkaz:
http://arxiv.org/abs/2402.10280
This paper introduces a novel approach, Decision Theory-guided Deep Reinforcement Learning (DT-guided DRL), to address the inherent cold start problem in DRL. By integrating decision theory principles, DT-guided DRL enhances agents' initial performan
Externí odkaz:
http://arxiv.org/abs/2402.06023
In this study, we explore the phenomenological signatures associated with a light fermiophobic Higgs boson, $h_{\rm f}$, within the type-I two-Higgs-doublet model at the HL-LHC. Our meticulous parameter scan illuminates an intriguing mass range for $
Externí odkaz:
http://arxiv.org/abs/2310.17741
Artificial neural networks (ANNs) have been broadly utilized to analyze various data and solve different domain problems. However, neural networks (NNs) have been considered a black box operation for years because their underlying computation and mea
Externí odkaz:
http://arxiv.org/abs/2310.01580
Autor:
Yu Jae-Seon, Jung Serang, Cho Jin-Woo, Park Geon-Tae, Kats Mikhail, Kim Sun-Kyung, Lee Eungkyu
Publikováno v:
Nanophotonics, Vol 13, Iss 21, Pp 4067-4078 (2024)
Achieving long-wavelength infrared (LWIR) cameras with high sensitivity and shorter exposure times faces challenges due to series reflections from high-refractive index lenses within compact optical systems. However, designing effective antireflectiv
Externí odkaz:
https://doaj.org/article/c97559f6e80e43f3b74ba70a5e8e66a1
Autor:
Guo, Zhen, Zhang, Qi, An, Xinwei, Zhang, Qisheng, Jøsang, Audun, Kaplan, Lance M., Chen, Feng, Jeong, Dong H., Cho, Jin-Hee
Due to various and serious adverse impacts of spreading fake news, it is often known that only people with malicious intent would propagate fake news. However, it is not necessarily true based on social science studies. Distinguishing the types of fa
Externí odkaz:
http://arxiv.org/abs/2302.10195