Zobrazeno 1 - 10
of 604
pro vyhledávání: '"Heng Wen"'
Publikováno v:
Zhongguo shuxue zazhi, Vol 35, Iss 12, Pp 1251-1255 (2022)
Objective To investigate the distribution of Hepatitis B virus(HBV)genotypes and the genetic characteristics of genotype B HBV populations among voluntary blood donors in five regions of China. Methods A total number of 630 plasma samples from blood
Externí odkaz:
https://doaj.org/article/da49cc4079d74738a43d32f0ba6d873b
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
Background: Lung adenocarcinoma (LUAD) is a life-threatening malignant tumor, contributing for the largest cancer burden worldwide. Tumor microenvironment (TME) is composed of various immune cells, stromal cells and tumor cells, which is highly assoc
Externí odkaz:
https://doaj.org/article/f1c19f8b41a44090afcabb60439374da
In this paper we present a novel method to estimate 3D human pose and shape from monocular videos. This task requires directly recovering pixel-alignment 3D human pose and body shape from monocular images or videos, which is challenging due to its in
Externí odkaz:
http://arxiv.org/abs/2303.00298
Publikováno v:
In Journal of Cleaner Production 5 January 2024 435
Real-time video frame interpolation (VFI) is very useful in video processing, media players, and display devices. We propose RIFE, a Real-time Intermediate Flow Estimation algorithm for VFI. To realize a high-quality flow-based VFI method, RIFE uses
Externí odkaz:
http://arxiv.org/abs/2011.06294
Autor:
Fang, Shih-Yu, Chen, Jeng-Wei, Chou, Heng-Wen, Chan, Chih-Yang, Wu, I-Hui, Chou, Nai-Kuan, Wang, Chih-Hsien, Chi, Nai-Hsin, Huang, Shu-Chien, Yu, Hsi-Yu, Chen, Yih-Sharng, Hsu, Ron-Bin
Publikováno v:
In Journal of the Formosan Medical Association December 2023 122(12):1265-1273
Autor:
Li, Hao-Ling, Wang, Jun-Xian, Dai, Heng-Wen, Liu, Jun-Jie, Liu, Zi-Yang, Zou, Ming-Yuan, Zhang, Lei *, Wang, Wen-Rui *
Publikováno v:
In Chinese Medical Sciences Journal September 2023 38(3):178-190
We revisit the one-shot Neural Architecture Search (NAS) paradigm and analyze its advantages over existing NAS approaches. Existing one-shot method, however, is hard to train and not yet effective on large scale datasets like ImageNet. This work prop
Externí odkaz:
http://arxiv.org/abs/1904.00420
We show how to teach machines to paint like human painters, who can use a small number of strokes to create fantastic paintings. By employing a neural renderer in model-based Deep Reinforcement Learning (DRL), our agents learn to determine the positi
Externí odkaz:
http://arxiv.org/abs/1903.04411