Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Mao, Yixiang"'
This work applies an encoder-decoder-based machine learning network to detect and track the motion and growth of the flowering stem apex of Arabidopsis Thaliana. Based on the CenterTrack, a machine learning back-end network, we trained a model based
Externí odkaz:
http://arxiv.org/abs/2405.11351
For $360^{\circ}$ video streaming, FoV-adaptive coding that allocates more bits for the predicted user's field of view (FoV) is an effective way to maximize the rendered video quality under the limited bandwidth. We develop a low-latency FoV-adaptive
Externí odkaz:
http://arxiv.org/abs/2403.11155
Many XR applications require the delivery of volumetric video to users with six degrees of freedom (6-DoF) movements. Point Cloud has become a popular volumetric video format. A dense point cloud consumes much higher bandwidth than a 2D/360 degree vi
Externí odkaz:
http://arxiv.org/abs/2303.08336
Octree-based point cloud representation and compression have been adopted by the MPEG G-PCC standard. However, it only uses handcrafted methods to predict the probability that a leaf node is non-empty, which is then used for entropy coding. We propos
Externí odkaz:
http://arxiv.org/abs/2209.02226
Autor:
Mao, Yixiang, Wu, Jiapeng, Yang, Ruotong, Ma, Yuexi, Ye, Jiaqi, Zhong, Jiarui, Deng, Nanling, He, Xiang, Hong, Yiguo
Publikováno v:
In Marine Environmental Research February 2024 194
Autor:
Mao, Yixiang
This thesis develops a new divergence that generalizes relative entropy and can be used to compare probability measures without a requirement of absolute continuity. We establish properties of the divergence, and in particular derive and exploit a re
Externí odkaz:
http://arxiv.org/abs/2011.08441
Autor:
Dupuis, Paul, Mao, Yixiang
This paper develops a new divergence that generalizes relative entropy and can be used to compare probability measures without a requirement of absolute continuity. We establish properties of the divergence, and in particular derive and exploit a rep
Externí odkaz:
http://arxiv.org/abs/1911.07422
Akademický článek
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Autor:
Dupuis, Paul1 (AUTHOR) paul_dupuis@brown.edu, Mao, Yixiang2 (AUTHOR)
Publikováno v:
ESAIM: Control, Optimisation & Calculus of Variations. 2022, Vol. 28, p1-38. 38p.
Autor:
Chen, Conan1 (AUTHOR) coc004@health.ucsd.edu, Mao, Yixiang1 (AUTHOR), Falahpour, Maryam1 (AUTHOR), MacNiven, Kelly H.2,3 (AUTHOR), Heit, Gary3,4 (AUTHOR), Sharma, Vivek3 (AUTHOR), Alataris, Konstantinos3 (AUTHOR), Liu, Thomas T.1 (AUTHOR) ttliu@health.ucsd.edu
Publikováno v:
Scientific Reports. 12/15/2021, Vol. 11 Issue 1, p1-8. 8p.