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Faculty of Scien... [3]
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ZHANG LIMING [2]
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Journal article [3]
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2024 [1]
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2022 [1]
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Level set guided region prototype rectification network for retinal vessel segmentation
Journal article
Liu, Yifei, Wu, Qingtian, Liu, Xueyu, Lu, Junyu, Xu, Zhenhuan, Wu, Yongfei, Feng, Shu. Level set guided region prototype rectification network for retinal vessel segmentation[J]. Biomedical Signal Processing and Control, 2024, 87, 105428.
Authors:
Liu, Yifei
;
Wu, Qingtian
;
Liu, Xueyu
;
Lu, Junyu
;
Xu, Zhenhuan
; et al.
Favorite
|
TC[WOS]:
0
TC[Scopus]:
1
IF:
4.9
/
4.9
|
Submit date:2024/02/22
Level-set
Region Prototype Rectification
Retinal Vessel Segmentation
Self-Supervised And Supervised Loss
Parallel Self-Attention and Spatial-Attention Fusion for Human Pose Estimation and Running Movement Recognition
Journal article
Wu,Qingtian, Zhang,Yu, Zhang,Liming, Yu,Haoyong. Parallel Self-Attention and Spatial-Attention Fusion for Human Pose Estimation and Running Movement Recognition[J]. IEEE Transactions on Cognitive and Developmental Systems, 2023, 16(1), 358-368.
Authors:
Wu,Qingtian
;
Zhang,Yu
;
Zhang,Liming
;
Yu,Haoyong
Favorite
|
TC[WOS]:
0
TC[Scopus]:
1
IF:
5.0
/
4.6
|
Submit date:2023/08/03
Convolutional Neural Networks
Feature Extraction
Feature Fusion
Human Pose Estimation
Pose Estimation
Running Recognition
Self-attention
Semantics
Spatial-attention
Task Analysis
Transformers
Visualization
A Local-Global Estimator based on Large Kernel CNN and Transformer for Human Pose Estimation and Running Pose Measurement
Journal article
Qingtian Wu, Yongfei Wu, Yu Zhang, Liming Zhang. A Local-Global Estimator based on Large Kernel CNN and Transformer for Human Pose Estimation and Running Pose Measurement[J]. IEEE transactions on Instrumentation and Instrumentation & Measurement, 2022, 71, 1-12.
Authors:
Qingtian Wu
;
Yongfei Wu
;
Yu Zhang
;
Liming Zhang
Favorite
|
TC[WOS]:
0
TC[Scopus]:
20
IF:
5.6
/
5.6
|
Submit date:2022/08/30
Convolutional Neural Networks (Cnn)
Human Pose Estimation (Hpe)
Local–global Estimator
Running Pose Measurement
Vision Transformer (Vit)