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文献类型:期刊论文
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Applying maximally stable extremal regions and local binary patterns for guide-wire detecting in percutaneous coronary intervention
期刊论文
IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 13, 页码: 2579-2586
作者:
Pusit, Prasong
;
Xie, Xiao-Liang
;
Hou, Zeng-Guang
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浏览/下载:339/72
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提交时间:2020/03/30
blood vessels
medical image processing
surgery
image sequences
video signal processing
image filtering
object detection
X-ray imaging
object tracking
stroke width variation filter
region detection
local binary patterns
guide-wire recognition
conventional MSER methods
maximally stable extremal regions
guide-wire position
anatomical skeleton contours
training data
X-ray video sequence
percutaneous coronary intervention surgery
region area range filter
X-ray video monitoring
guide-wire tip detection
modified multifilters
training templates
Deep Hierarchical Encoder-Decoder Network for Image Captioning
期刊论文
IEEE TRANSACTIONS ON MULTIMEDIA, 2019, 卷号: 21, 期号: 11, 页码: 2942-2956
作者:
Xiao, Xinyu
;
Wang, Lingfeng
;
Ding, Kun
;
Xiang, Shiming
;
Pan, Chunhong
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浏览/下载:295/0
  |  
提交时间:2020/03/30
Visualization
Semantics
Hidden Markov models
Decoding
Logic gates
Training
Computer architecture
Deep hierarchical structure
encoder-decoder
LSTM
image captioning
retrieval
vision-sentence
A hierarchical contextual attention-based network for sequential recommendation
期刊论文
NEUROCOMPUTING, 2019, 卷号: 358, 页码: 141-149
作者:
Cui, Qiang
;
Wu, Shu
;
Huang, Yan
;
Wang, Liang
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浏览/下载:272/28
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提交时间:2019/05/09
Sequential recommendation
Recurrent neural network
Short-term interest
Context
Attention mechanism
Two-Level Attention Network With Multi-Grain Ranking Loss for Vehicle Re-Identification
期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 9, 页码: 4328-4338
作者:
Guo, Haiyun
;
Zhu, Kuan
;
Tang, Ming
;
Wang, Jinqiao
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浏览/下载:330/67
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提交时间:2019/12/16
Two-level attention network
multi-grain ranking loss
vehicle re-identification
feature embedding
A robotic shared control teleoperation method based on learning from demonstrations
期刊论文
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2019, 卷号: 16, 期号: 4, 页码: 1-13
作者:
Xi, Bao
;
Wang, Shuo
;
Ye, Xuemei
;
Cai, Yinghao
;
Lu, Tao
;
Wang, Rui
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浏览/下载:368/61
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提交时间:2019/12/16
Dual arm
hidden semi-Markov model
goal prediction
operation assistance
virtual reality
Scene text detection and recognition with advances in deep learning: a survey
期刊论文
INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, 2019, 卷号: 22, 期号: 2, 页码: 143-162
作者:
Liu, Xiyan
;
Meng, Gaofeng
;
Pan, Chunhong
Adobe PDF(2418Kb)
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浏览/下载:278/30
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提交时间:2019/07/11
Natural image
Text detection
Text recognition
Survey
Robotic Skill Learning for Precision Assembly With Microscopic Vision and Force Feedback
期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2019, 卷号: 24, 期号: 3, 页码: 1117-1128
作者:
Qin, Fangbo
;
Xu, De
;
Zhang, Dapeng
;
Li, Ying
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浏览/下载:515/196
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提交时间:2019/05/06
Force control
learning from demonstration
microscopic vision
precision assembly
robotic skill learning
Learning view invariant gait features with Two-Stream GAN
期刊论文
NEUROCOMPUTING, 2019, 卷号: 339, 期号: 2019, 页码: 245-254
作者:
Wang, Yanyun
;
Song, Chunfeng
;
Huang, Yan
;
Wang, Zhenyu
;
Wang, Liang
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Adobe PDF(2222Kb)
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浏览/下载:484/139
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提交时间:2019/07/12
Gait recognition
Cross-veiw
Two-Stream GAN
Analysis of Interventionalists' Natural Behaviors for Recognizing Motion Patterns of Endovascular Tools During Percutaneous Coronary Interventions
期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, 2019, 卷号: 13, 期号: 2, 页码: 330-342
作者:
Zhou, Xiao-Hu
;
Bian, Gui-Bin
;
Xie, Xiao-Liang
;
Hou, Zeng-Guang
;
Qu, Xinkai
;
Guan, Shaofeng
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浏览/下载:528/148
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提交时间:2019/04/23
Analysis framework
hidden Markov model
hierarchical classification framework
natural behaviors
percutaneous coronary intervention
Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving
期刊论文
IEEE Computational Intelligence Magazine, IEEE Computational Intelligence Magazine, 2019, 2019, 卷号: 14, 14, 期号: 2, 页码: 83-98, 83-98
作者:
Dong Li
;
Dongbin Zhao
;
Qichao Zhang
;
Yaran Chen
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浏览/下载:355/102
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提交时间:2019/04/25
Deep Learning
Autonomous Driving
Visual Control
Reinforcement Learning
Deep Learning
Autonomous Driving
Visual Control
Reinforcement Learning