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Research Publications - Air and Space

Select a Topic:​ All​ Motion Analysis​ Character Animation​​ Interaction Modelling​ Video Analysis​ Action Recognition​ 3D Reconstruction​ Healthcare Diagnosis​ Crowd Modelling​ Environment Sensing​ Virtual Reality​ Surface Modelling​ Face Modelling​ Responsible AI​ Robotics​ Hands and Gestures​ Surveillance​ Cybersecurity​ Artwork Analysis​ Medical Imaging​ Air and Space​​

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As a part of Durham University Space Research Centre, we study the computer science aspects of space technologies, as well as the complementary air capacity such as the controls and detection of unmanned aerial vehicles (UAVs). This research is supported by my Ministry of Defence (DASA) project and my UK Catapult Network project.

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2023

A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments
A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments     Core A* Conference‡ 
Proceedings of the 2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), 2023
Kanglei Zhou, Chen Chen, Yue Ma, Zhiying Leng, Hubert P. H. Shum, Frederick W. B. Li and Xiaohui Liang
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2022

Formation Control for UAVs Using a Flux Guided Approach
Formation Control for UAVs Using a Flux Guided Approach  Impact Factor: 7.5† Top 25% Journal in Computer Science, Artificial Intelligence†   
Expert Systems with Applications (ESWA), 2022
John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang and Subramanian Ramamoorthy
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UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery
UAV-ReID: A Benchmark on Unmanned Aerial Vehicle Re-Identification in Video Imagery      
Proceedings of the 2022 International Conference on Computer Vision Theory and Applications (VISAPP), 2022
Daniel Organisciak, Matthew Poyser, Aishah Alsehaim, Shanfeng Hu, Brian K. S. Isaac-Medina, Toby P. Breckon and Hubert P. H. Shum
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2021

Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark
Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark    H5-Index: 80#  Citation: 88#
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021
Brian K. S. Isaac-Medina, Matthew Poyser, Daniel Organisciak, Chris G. Willcocks, Toby P. Breckon and Hubert P. H. Shum
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† According to Journal Citation Reports 2023
‡ According to Core Ranking 2023
# According to Google Scholar 2024

 

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