Zobrazeno 1 - 10
of 13 265
pro vyhledávání: '"An, Haowen"'
Autor:
Xu, Shuang, Zhao, Zixiang, Bai, Haowen, Yu, Chang, Peng, Jiangjun, Cao, Xiangyong, Meng, Deyu
Hyperspectral images (HSIs) are frequently noisy and of low resolution due to the constraints of imaging devices. Recently launched satellites can concurrently acquire HSIs and panchromatic (PAN) images, enabling the restoration of HSIs to generate c
Externí odkaz:
http://arxiv.org/abs/2412.04201
Particle velocimetry is essential in solid fuel combustion studies, however, the accurate detection and tracking of particles in high Particle Number Density (PND) combustion scenario remain challenging. The current study advances the machine-learnin
Externí odkaz:
http://arxiv.org/abs/2412.04091
Autor:
Jiang, Min, Su, Haowen, Chen, Yifan, Jiao, Man, Huang, Ying, Wang, Yuanhong, Rong, Xing, Peng, Xinhua, Du, Jiangfeng
Numerous theories have postulated the existence of exotic spin-dependent interactions beyond the Standard Model of particle physics. Spin-based quantum sensors, which utilize the quantum properties of spins to enhance measurement precision, emerge as
Externí odkaz:
http://arxiv.org/abs/2412.03288
Autor:
Bai, Haowen, Zhang, Jiangshe, Zhao, Zixiang, Wu, Yichen, Deng, Lilun, Cui, Yukun, Feng, Tao, Xu, Shuang
Multi-modal image fusion aggregates information from multiple sensor sources, achieving superior visual quality and perceptual characteristics compared to any single source, often enhancing downstream tasks. However, current fusion methods for downst
Externí odkaz:
http://arxiv.org/abs/2412.03240
In the evolving digital landscape, network flow models have transcended traditional applications to become integral in diverse sectors, including supply chain management. This research develops a robust network flow model for semiconductor wafer supp
Externí odkaz:
http://arxiv.org/abs/2411.17544
Autor:
Zheng, Haowen, Liang, Yanyan
Recent advancements in 3D diffusion-based semantic scene generation have gained attention. However, existing methods rely on unconditional generation and require multiple resampling steps when editing scenes, which significantly limits their controll
Externí odkaz:
http://arxiv.org/abs/2411.12290
By treating intervals as inseparable sets, this paper proposes sparse machine learning regressions for high-dimensional interval-valued time series. With LASSO or adaptive LASSO techniques, we develop a penalized minimum distance estimation, which co
Externí odkaz:
http://arxiv.org/abs/2411.09452
Topic modeling, or more broadly, dimensionality reduction, techniques provide powerful tools for uncovering patterns in large datasets and are widely applied across various domains. We investigate how Non-negative Matrix Factorization (NMF) can intro
Externí odkaz:
http://arxiv.org/abs/2411.09847
Autor:
Lao, Guanming, Khvorost, Taras, Macias, Jr., Antonio, Morgan, Harry W. T., Lavroff, Robert H., Choi, Ryan, Zhou, Haowen, Usvyat, Denis, Zhu, Guo-Zhu, García-Garibay, Miguel A., Alexandrova, Anastassia N., Hudson, Eric R., Campbell, Wesley C.
Gas-phase molecules capable of repeatable, narrow-band spontaneous photon scattering are prized for direct laser cooling and quantum state detection. Recently, large molecules incorporating phenyl rings have been shown to exhibit similar vibrational
Externí odkaz:
http://arxiv.org/abs/2411.03199
Autor:
Chen, Chunlu, Liu, Ji, Tan, Haowen, Li, Xingjian, Wang, Kevin I-Kai, Li, Peng, Sakurai, Kouichi, Dou, Dejing
While recent years have witnessed the advancement in big data and Artificial Intelligence (AI), it is of much importance to safeguard data privacy and security. As an innovative approach, Federated Learning (FL) addresses these concerns by facilitati
Externí odkaz:
http://arxiv.org/abs/2411.01583