Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Yuanhao Cai"'
Autor:
Yuanhao Cai, Weilin Wang, Liang Li, Zhaofeng Wang, Suying Wang, Hao Ding, Zhengguo Zhang, Luyi Sun, Weixing Wang
Publikováno v:
Materials, Vol 11, Iss 2, p 183 (2018)
The emission of CO2 has been considered a major cause of greenhouse effects and global warming. The current CO2 capture approaches have their own advantages and weaknesses. We found that free-flowing hydrated sodium carbonate (Na2CO3) powders with 30
Externí odkaz:
https://doaj.org/article/c1bf2acadffb40b6900cfb31a010f54a
Autor:
Zhuo Deng, Yuanhao Cai, Lu Chen, Zheng Gong, Qiqi Bao, Xue Yao, Dong Fang, Wenming Yang, Shaochong Zhang, Lan Ma
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 26:4645-4655
Ophthalmologists have used fundus images to screen and diagnose eye diseases. However, different equipments and ophthalmologists pose large variations to the quality of fundus images. Low-quality (LQ) degraded fundus images easily lead to uncertainty
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::128ca56ea16b73d6f431d5b02ece1a8c
https://doi.org/10.1109/jbhi.2022.3187103
https://doi.org/10.1109/jbhi.2022.3187103
Autor:
Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc Van Gool
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system. The HSI representations are highly similar and correlated across the spectra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4918b28b1ce51cd6d1cfa9e2d6ba61a
https://doi.org/10.1109/cvpr52688.2022.01698
https://doi.org/10.1109/cvpr52688.2022.01698
Autor:
Xiaowan Hu, Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc Van Gool
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
The rapid development of deep learning provides a better solution for the end-to-end reconstruction of hyperspectral image (HSI). However, existing learning-based methods have two major defects. Firstly, networks with self-attention usually sacrifice
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de21031a2e293bc1f488ebfb7265bda8
https://doi.org/10.1109/cvpr52688.2022.01702
https://doi.org/10.1109/cvpr52688.2022.01702
Autor:
Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Radu Timofte, Luc Van Gool
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or wider convolutional neural networks (CNNs) to learn the end-to-end mapping from the RGB image to its hyperspectral image (HSI). These CNN-based methods achieve imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e087b6ae9c83bfc84943fe9688fc2f44
https://doi.org/10.1109/cvprw56347.2022.00090
https://doi.org/10.1109/cvprw56347.2022.00090
Autor:
Yuanhao Cai, Jing Lin, Xiaowan Hu, Haoqian Wang, Xin Yuan, Yulun Zhang, Radu Timofte, Luc Van Gool
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197895
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a080e995433ed613ff26346db3db68b
https://doi.org/10.1007/978-3-031-19790-1_41
https://doi.org/10.1007/978-3-031-19790-1_41
Autor:
Boaz Arad, Radu Timofte, Rony Yahel, Nimrod Morag, Amir Bernat, Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Luc Van Gool, Shuai Liu, Yongqiang Li, Chaoyu Feng, Lei Lei, Jiaojiao Li, Songcheng Du, Chaoxiong Wu, Yihong Leng, Rui Song, Mingwei Zhang, Chongxing Song, Shuyi Zhao, Zhiqiang Lang, Wei Wei, Lei Zhang, Renwei Dian, Tianci Shan, Anjing Guo, Chengguo Feng, Jinyang Liu, Mirko Agarla, Simone Bianco, Marco Buzzelli, Luigi Celona, Raimondo Schettini, Jiang He, Yi Xiao, Jiajun Xiao, Qiangqiang Yuan, Jie Li, Liangpei Zhang, Taesung Kwon, Dohoon Ryu, Hyokyoung Bae, Hao-Hsiang Yang, Hua-En Chang, Zhi-Kai Huang, Wei-Ting Chen, Sy-Yen Kuo, Junyu Chen, Haiwei Li, Song Liu, Sabarinathan Sabarinathan, K Uma, B Sathya Bama, S. Mohamed Mansoor Roomi
This paper reviews the third biennial challenge on spectral reconstruction from RGB images, i.e., the recovery of whole-scene hyperspectral (HS) information from a 3-channel RGB image. This challenge presents the "ARAD_1K"data set: a new, larger-than
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b14c6f9646b01a471ce946e43634fa64
http://hdl.handle.net/11583/2971543
http://hdl.handle.net/11583/2971543
Publikováno v:
Journal of Photochemistry and Photobiology B: Biology. 234:112541
Acute lung injury (ALI) impaired the function of blood oxygen exchange function, resulting in tissue hypoxia and patient death. Recently, human umbilical cord mesenchymal stem cells (hUCMSCs) are thought to mitigate the effects of ALI, which boosts r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eedd5c6e2d343fae9274ac8554bee565
https://doi.org/10.1016/j.jphotobiol.2022.112541
https://doi.org/10.1016/j.jphotobiol.2022.112541
Publikováno v:
IJCAI
The feedback mechanism in the human visual system extracts high-level semantics from noisy scenes. It then guides low-level noise removal, which has not been fully explored in image denoising networks based on deep learning. The commonly used fully-s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::235382c1f0fafa8a27b495aa59410d10
https://doi.org/10.24963/ijcai.2021/101
https://doi.org/10.24963/ijcai.2021/101
Publikováno v:
2021 IEEE International Conference on Multimedia and Expo (ICME).
For magnetic resonance (MR) images sharing visual characteristics, the internal structure repetitions of different scales are considerable image-specific priors. Following the traditional algorithms, we try to combine external dataset-driven learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0e9ef4d12a29a45785a9a92da4d1281
https://doi.org/10.1109/icme51207.2021.9428112
https://doi.org/10.1109/icme51207.2021.9428112