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共11条,第1-10条
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发表日期:2020
资助机构:National Natural Science Foundation of China
文献类型:期刊论文
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Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics
期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3585-3594
作者:
Li, Cong
;
Dong, Di
;
Li, Liang
;
Gong, Wei
;
Li, Xiaohu
;
Bai, Yan
;
Wang, Meiyun
;
Hu, Zhenhua
;
Zha, Yunfei
;
Tian, Jie
Adobe PDF(2325Kb)
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收藏
  |  
浏览/下载:428/65
  |  
提交时间:2021/03/02
COVID-19
radiomics
deep learning
computed tomography (CT)
An Interventionalist-Behavior-Based Data Fusion Framework for Guidewire Tracking in Percutaneous Coronary Intervention
期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2020, 卷号: 50, 期号: 11, 页码: 4836-4849
作者:
Zhou, Xiao-Hu
;
Bian, Gui-Bin
;
Xie, Xiao-Liang
;
Hou, Zeng-Guang
收藏
  |  
浏览/下载:317/0
  |  
提交时间:2021/01/07
Tracking
Sensors
Tools
Catheters
Electromyography
Data integration
Frequency modulation
Data fusion framework
guidewire tracking
interventionalist behavior
percutaneous coronary intervention (PCI)
Automatic segmentation of intracerebral hemorrhage in CT images using encoder-decoder convolutional neural network
期刊论文
INFORMATION PROCESSING & MANAGEMENT, 2020, 卷号: 57, 期号: 6, 页码: 16
作者:
Hu, Kai
;
Chen, Kai
;
He, Xizhi
;
Zhang, Yuan
;
Chen, Zhineng
;
Li, Xuanya
;
Gao, Xieping
收藏
  |  
浏览/下载:238/0
  |  
提交时间:2021/01/06
Intracerebral hemorrhage
Segmentation
Convolutional neural networks
Multi-scale features
Data imbalance
Pyramid attention recurrent networks for real-time guidewire segmentation and tracking in intraoperative X-ray fluoroscopy
期刊论文
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2020, 卷号: 83, 页码: 9
作者:
Zhou, Yan-Jie
;
Xie, Xiao-Liang
;
Zhou, Xiao-Hu
;
Liu, Shi-Qi
;
Bian, Gui-Bin
;
Hou, Zeng-Guang
收藏
  |  
浏览/下载:265/0
  |  
提交时间:2020/08/24
Guidewire
Catheter
Segmentation
Deep learning
X-ray fluoroscopy
Reconstruction of lines and planes of urban buildings with angle regularization
期刊论文
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2020, 卷号: 165, 页码: 54-66
作者:
Wang, Wei
;
Gao, Wei
;
Cui, Hainan
;
Hu, Zhanyi
收藏
  |  
浏览/下载:270/0
  |  
提交时间:2020/07/20
Line segment matching
Multi-model fitting
3D reconstruction
Convolutional neural network
Reconstruction of lines and planes of urban buildings with angle regularization
期刊论文
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2020, 卷号: 165, 页码: 54-66
作者:
Wang, Wei
;
Gao, Wei
;
Cui, Hainan
;
Hu, Zhanyi
收藏
  |  
浏览/下载:248/0
  |  
提交时间:2020/07/20
Line segment matching
Multi-model fitting
3D reconstruction
Convolutional neural network
Non-uniqueness Phenomenon of Object Representation in Modeling IT Cortex by Deep Convolutional Neural Network (DCNN)
期刊论文
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2020, 卷号: 14, 页码: 9
作者:
Dong, Qiulei
;
Liu, Bo
;
Hu, Zhanyi
Adobe PDF(748Kb)
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收藏
  |  
浏览/下载:357/73
  |  
提交时间:2020/06/22
deep convolutional neural network
neural object representation
inferotemporal cortex
non-uniqueness
image object representation
Effective piecewise planar modeling based on sparse 3D points and convolutional neural network
期刊论文
NEUROCOMPUTING, 2020, 卷号: 378, 页码: 350-363
作者:
Wang, Wei
;
Gao, Wei
;
Hu, Zhanyi
收藏
  |  
浏览/下载:275/0
  |  
提交时间:2020/03/30
Urban scene
Piecewise planar stereo
Markov Random Field
Image over-segmentation
Convolutional neural network
Attention-Based Two-Stream Convolutional Networks for Face Spoofing Detection
期刊论文
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2020, 卷号: 15, 页码: 578-593
作者:
Chen, Haonan
;
Hu, Guosheng
;
Lei, Zhen
;
Chen, Yaowu
;
Robertson, Neil M.
;
Li, Stan Z.
收藏
  |  
浏览/下载:264/0
  |  
提交时间:2020/03/30
Face spoofing
multi-scale retinex
deep learning
attention model
feature fusion
Qualitative and Quantitative Assessment of Technical Skills in Percutaneous Coronary Intervention: In Vivo Porcine Studies
期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 卷号: 67, 期号: 2, 页码: 353-364
作者:
Zhou, Xiao-Hu
;
Bian, Gui-Bin
;
Xie, Xiao-Liang
;
Hou, Zeng-Guang
;
Li, Rui-Qi
;
Zhou, Yan-Jie
收藏
  |  
浏览/下载:344/0
  |  
提交时间:2020/03/30
Natural behaviors
percutaneous coronary intervention
assessment framework
qualitative and quantitative assessment
in vivo porcine studies