Hui Zhang

Orcid: 0000-0001-8012-4684

Affiliations:
  • Beijing University of Technology, Faculty of Information Technology, Beijing Key Laboratory Computational Intelligence and Intelligent System, Beijing, China


According to our database1, Hui Zhang authored at least 26 papers between 2016 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2022
Detecting Absence of Bone Wall in Jugular Bulb by Image Transformation Surrogate Tasks.
IEEE Trans. Medical Imaging, 2022

Streamer temporal action detection in live video by co-attention boundary matching.
Int. J. Mach. Learn. Cybern., 2022

Polyp segmentation network with hybrid channel-spatial attention and pyramid global context guided feature fusion.
Comput. Medical Imaging Graph., 2022

2021
MultiRPN-DIDNet: Multiple RPNs and Distance-IoU Discriminative Network for Real-Time UAV Target Tracking.
Remote. Sens., 2021

Vestibule segmentation from CT images with integration of multiple deep feature fusion strategies.
Comput. Medical Imaging Graph., 2021

2020
Object Tracking in RGB-T Videos Using Modal-Aware Attention Network and Competitive Learning.
Sensors, 2020

Object Tracking in Unmanned Aerial Vehicle Videos via Multifeature Discrimination and Instance-Aware Attention Network.
Remote. Sens., 2020

A 3D deep supervised densely network for small organs of human temporal bone segmentation in CT images.
Neural Networks, 2020

Multi-level prediction Siamese network for real-time UAV visual tracking.
Image Vis. Comput., 2020

A lateral semicircular canal segmentation based geometric calibration for human temporal bone CT Image.
CoRR, 2020

TISNet-Enhanced Fully Convolutional Network with Encoder-Decoder Structure for Tongue Image Segmentation in Traditional Chinese Medicine.
Comput. Math. Methods Medicine, 2020

Key-Point Matching Guided Coronary Artery Extraction from CT Coronary Angiography Sequence.
Proceedings of the 13th International Congress on Image and Signal Processing, 2020

2019
Long-Term Visual Object Tracking via Continual Learning.
IEEE Access, 2019

2018
Vehicle color recognition using Multiple-Layer Feature Representations of lightweight convolutional neural network.
Signal Process., 2018

High-accuracy vehicle color recognition using hierarchical fine-tuning strategy for urban surveillance videos.
J. Electronic Imaging, 2018

Feature extraction using lightweight convolutional network for vehicle classification.
J. Electronic Imaging, 2018

Dccn: A Deep-Color Correction Network For Traditional Chinese Medicine Tongue Images.
Proceedings of the 2018 IEEE International Conference on Multimedia & Expo Workshops, 2018

Visual Tracking with Bounding-Box Fine Adjustment.
Proceedings of the 11th International Congress on Image and Signal Processing, 2018

A 3D Fully Convolutional Network Based Semantic Segmentation for Ear Computed Tomography Images.
Proceedings of the 11th International Congress on Image and Signal Processing, 2018

Fine-grained Vehicle Recognition Using Lightweight Convolutional Neural Network with Combined Learning Strategy.
Proceedings of the Fourth IEEE International Conference on Multimedia Big Data, 2018

2017
Extracting Deep Video Feature for Mobile Video Classification with ELU-3DCNN.
Proceedings of the Internet Multimedia Computing and Service, 2017

Automatic Tongue Image Segmentation for Traditional Chinese Medicine Using Deep Neural Network.
Proceedings of the Intelligent Computing Theories and Application, 2017

Pedestrian Detection Based on Imbalance Prior for Surveillance Video.
Proceedings of the 2017 International Conference on Digital Image Computing: Techniques and Applications, 2017

A gradient-domain image enhancement method for traffic signs in nighttime surveillance.
Proceedings of the 10th International Congress on Image and Signal Processing, 2017

2016
Improved target tracking based on spatio-temporal learning.
Proceedings of the IEEE International Conference on Information and Automation, 2016

Mechanical arm grasping and target recognition strategy based on the coarse-to-fine algorithm.
Proceedings of the IEEE International Conference on Information and Automation, 2016


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