Zobrazeno 1 - 10
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pro vyhledávání: '"Dèng, Fēi"'
Autor:
Deng, Fei
Publikováno v:
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Thesis (Ph. D.)--University of California, San Diego, 1997.
Vita. Includes bibliographical references (leaves 151-153).
Vita. Includes bibliographical references (leaves 151-153).
Externí odkaz:
http://wwwlib.umi.com/cr/ucsd/fullcit?p9820863
Autor:
Deng, Feifei
Thorium-230 and protactinium-231 have been widely used as proxies of oceanic processes in both modern and past marine environment. Their application as such proxies is, however, limited by sparse data from the modern ocean with which to characterize
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.655073
Semantic segmentation of remote sensing (RS) images is a challenging yet crucial task. While deep learning, particularly supervised learning with large-scale labeled datasets, has significantly advanced this field, acquiring high-quality labeled data
Externí odkaz:
http://arxiv.org/abs/2410.13471
Autor:
Jiang, Peifan, Wang, Xuben, Wang, Shuang, Deng, Fei, Wang, Kunpeng, Wang, Bin, Yang, Yuhan, Fadel, Islam
Magnetotelluric deep learning (DL) inversion methods based on joint data-driven and physics-driven have become a hot topic in recent years. When mapping observation data (or forward modeling data) to the resistivity model using neural networks (NNs),
Externí odkaz:
http://arxiv.org/abs/2410.09388
Recent State Space Models (SSMs) such as S4, S5, and Mamba have shown remarkable computational benefits in long-range temporal dependency modeling. However, in many sequence modeling problems, the underlying process is inherently modular and it is of
Externí odkaz:
http://arxiv.org/abs/2406.12272
Despite the recent advancements in offline RL, no unified algorithm could achieve superior performance across a broad range of tasks. Offline \textit{value function learning}, in particular, struggles with sparse-reward, long-horizon tasks due to the
Externí odkaz:
http://arxiv.org/abs/2406.06793
Low-dose computed tomography (LDCT) has become the technology of choice for diagnostic medical imaging, given its lower radiation dose compared to standard CT, despite increasing image noise and potentially affecting diagnostic accuracy. To address t
Externí odkaz:
http://arxiv.org/abs/2404.09533
Electroencephalogram (EEG) signals play a pivotal role in clinical medicine, brain research, and neurological disease studies. However, susceptibility to various physiological and environmental artifacts introduces noise in recorded EEG data, impedin
Externí odkaz:
http://arxiv.org/abs/2404.15289
Geographical, physical, or economic constraints often result in missing traces within seismic data, making the reconstruction of complete seismic data a crucial step in seismic data processing. Traditional methods for seismic data reconstruction requ
Externí odkaz:
http://arxiv.org/abs/2403.11482