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Computer Science

Photo of Prof Chunbo Luo

Prof Chunbo Luo

Associate Professor in Computer Science

 (Streatham) 5725

 01392 725725



Prof Luo's current research interests lie in the machine learning methods for remote sensing and Earth observation. These scientific investigations have real-world applications in areas such as natural disaster prediction, management, and environment protection. Examples include the detection of algal blooms, tracking of marine carbon flux, and detection of marine oil spills etc. My work greatly benefits from collaborative research with leading research institutes, including the Plymouth Marine Laboratory, the Met Office, and the National Oceanographic Centre.

Prof Luo has organized and/or chaired (with other leading researchers) 11 conferences/workshops, including The 17th IEEE International Conference on Big Data Science and Engineering; The 20th International Conference on Computer and Information Technology; The 10th IEEE International Conference on Big Data and Cloud Computing; The 4th IEEE International Conference on Data Science and Systems; The 14th International Symposium on Pervasive Systems, Algorithms, and Networks; International Symposium on Advances in Data Science and Technologies; International Symposium on Advanced Topics in Pervasive Computing and Networking Technologies; The Machine Learning for Earth Observations in Exeter(2023, 2024); The BMVC workshop on Machine Vision for Earth Observation (2023, 2024).


  • Try my supervised project completed by Haoyang on classifiying land covers using deep learning models, and compare the changes happend in history
  • Machine learning for Earth Observation Workshop 2024 will be held in Exeter on 24/25 June. Click here to register the workshop! 
  • We have 2 papers focusing on machine learning for remote sensing image processing accepted in IEEE International Symposium on Geoscience and Remote Sensing 2024 (IGARSS 2024). 
  • We have 2 papers on the smart sensor networks for land movement detection and machine learning methods for environment data processing accepted in EGU 2024! Congratulations to all! 
  • Our paper published in IEEE Network Magazine is avaialbe: Ubiquitous and Robust UxV Networks: Overviews, Solutions, Challenges, and Opportunities
  • Our remote sensing data processing and machine learning pipeline with code tools will be available soon. 
  • Congratulatios to the final workshop for the NERC funded SENSUM project (5 Dec 2023),  Thanks to all speakers.
  • Our BMVC 2023 workshop on Machine Vision for Earth Observations is today (24 Nov 2023) Click here to attend! Many thanks to all the organizing committees for their outstanding efforts.
  • EPSRC PhD studentships: (If you are interested in AI/ML for Earth Observations, please send me an email to co-write a proposal.)
  • We are proud to announce the 17th IEEE International Conference on Big Data Science and Engineering and joint conferences, to be held in Exeter from 1 November to 3 November 2023. 
  • 欢迎2023年优秀学生申请PhD奖学金(包括CSC scholarship等, 50个全额奖学金机会),研究课题(Machine learning and intelligent sensing methods for Earth observations; Interpretable methods for remote sensing data collection and processing etc.)可参考下面的课题等。
  • Pleased to announce one NERC funded GW4+ PhD studentship opportunity: Click
  • Congratulations to our data science professional programme - we will be the primary apprenticeship provider for the BBC.
  • 4 top journal papers (Remote Sensing of Environment (IF 10.1), Science of the Total Environment (IF 10.15), IEEE Trans on Industry Informatics (IF 10.2), IEEE Internet of Things Journal (IF 11.7)) were recently accepted.
  • A new project on Machine learning methods for high resolution aerial sensing data processing to be funded by the EPSRC iCASE with OS.
  • The 17th IEEE International Conference on Big Data Science and Engineering (BigDataSE-2023) and sister conferences are calling for papers. 
  • Our project A rapid assessment tool for Woodland Creation investment to the competition Feasibility studies for Artificial Intelligence solutions will be funded. 
  • Our EU Horizon project (REFINE) for air quality monitoring using drones is going to be funded (May 2023).
  • Our AI for the Global Goals project with PML scientists passed the interview stage. 
  • We are excited to announce the workshop on "Machine learning for remote sensing" to be held in the University of Exeter, on 20-21 April 2023. 
  • Our projects "Integrating UAVs and social sensing for timely flooding warning in coastal areas" and "Robust and Agile Monitoring and Communication in Remote Sensing for Efficient Geological Hazard Prevention" to be funded by the Royal Society in 2023.
  • Our papers were accepted in the European Geosciences Union (EGU ) 2023 conference, to be held in Vienna, Austria, on 23 April. (Smart sensors to detect movements of cobbles and large woody debris dams. Insights from lab experiments, by Alessandro Sgarabotto et al.; Smart cobbles and boulders for monitoring movement in rivers and on hillslopes by Kyle Roskilly et al.)
  • Glad to receive the student feedback report for my module ECM3428 Algorithms that changed the world, which received overwhelmingly positive feedback and has a total score of 4.72 out of 5. Enjoyed teaching our talented students again.  


  • Research Manager: EU Horizon 2020 project: Intelligent and Sustainable Aerial-Terrestrial IoT Networks
  • Theme lead:  Remote Sensing, Institute for Data Science and Artificial Intelligence (IDSAI)
  • Steering commitee member of NERC NEODAAS


Some industrial projects I have worked on include:

  • Using remote sensing data (satellite imagery) to automate the rebuidling insurance estimation. This is a project with RiskStop to use machine learning/remote sensing techniques.
  • Using machine learning methods with remote sensing data for woorland creation. This is a project with Space Clipper to assess suitability of woodlands creation using ML and Earth observations. 

Current projects

  • Integrating Remote Sensing and Social Sensing for Timely Flooding Warning in Coastal Areas, Royal Society, 2023-2025, PI. 
  • Intelligent Satellite Remote Sensing for Real-Time Accurate Geological Hazard Analysis, Royal Society, 2023-2025, CoI
  • UKRI KTN. Automated insurance rebuilds cost estimate for residential and commercial properties, with RCA, Ref: 10031767, 10/2022-09/2024.  
  • EU H2020. INITIATE: Intelligent and Sustainable Aerial-Terrestrial IoT Networks, 101008297,  01/2022-12/2025, CoI.
  • NERC. SENSUM: smart SENSing of landscapes Undergoing hazardous hydrogeologic Movement, NE/V003402/1, 10/2020-09/2023, CoI

Previous projects (from 2015)

  • DeepWater: Remote sensing and DEEP learning for early warning of WATER quality hazards, Plymouth Marine Laboratory and ESA (Dragon 4), £60,869.57, 09/2018-07/2022, PI
  • NERC. BigFoot: BIG data methods for improving windstorm FOOTprint prediction, NE/P017436/1, £1,530,230, 2017-2021, CoI
  • KTP (Knowledge Transfer). Research on Key Communication Technologies to Transmit High-Definition Video, Contract No: H02016050002CG, £54,794, 01/08/2017 – 31/07/2018, PI
  • KTP (Knowledge Transfer). High-Performance Distributed Algorithms and Key Technologies for Processing SDN Big Data, Huawei Technologies, Contract No: YBN2016080110, £223,200, 08/2017 – 10/2021, CoI
  • ESRC IAA. Building Digital Identities: A Scoping Study, Social Policy Network, 2017-2018, CoI. LinkReport
  • Royal Society of Edinburgh. Flood Detection and Monitoring using Hyperspectral Remote Sensing from Unmanned Aerial Vehicles, £19,950K, 2016-2018, CoI
  • Feasibility study on a fully deployable resilient flooding predicting, monitoring and response system, Exeter EMPS ADR funding, 2016-2017, PI.
  • China UK Technology Innovation Centre Workshop 2016 (with Prof G Parr, University of East Anglia, and other 7 UK universities, Prof W Chen of Tsinghua University, Shanghai Jiaotong University and other 3 China research institutes, as well as Prof N Azarmi BT and other 4 industrial partners). Link
  • EU Horizon 2020. SELFNET Framework for Self-organized Network Management in Virtualized and Software Defined Networks, €6.8M, 2015-2017, Co-I.
  • 2016 Exeter-Tsinghua Outward Mobility Academic Fellowship
  • EPSRC Digital Economy: A Pilot Study on a Fully Deployable Cooperative Unmanned Aerial Vehicles System for Flooding Prediction, Monitoring and Response Services, PI.
  • Royal Society. Research on Multiple UAV Cooperation for Marine Oil Spill Detection, PI. 

Some recent talks

  • 2021 UK-China collaborative workshop: AI for Climate, Environment and Sustainability 
  • 2021 PML-Exeter joint workshop on Change Detection for Very High Resolution (VHR) Remote Sensing 
  • 2020 18th IEEE ISPA Machine Learning empowered Future Network Workshop Keynote Talk: Machine Learning for Communication and Network Data Processing
  • 2019 BT Thought Leadership Talk Forum

PhD projects(博士研究和奖学金机会)

Highly motivated postgraduate students are welcome to apply for PhDs. I am offering to supervise self-funded PhD students in the areas of:

  • Machine/deep learning methods
  • Image and data processing
  • Earth observation and remote sensing

Previous group members

  • Dr James Nightingale - Teaching fellow, University of Strathclyde
  • Dr Huaizhong Zhang - Senior Lecturer, Edge Hill University
  • Dr Qin Zhang - Associate Professor, Qingdao Agricultural University
  • Dr Sami Alenezi - Faculty member, North Border University
  • Dr Leonhard Menz - Head of Process, Porsche AG
  • Dr Yang Mi - Postdoc RA, The Hong Kong Polytechnic University
  • Dr Nicholas Kirk - Lead Investor @ Vehiculum Capital
  • Mr Stephen Goult - Machine Learning Development Software Engineer, Spirent Communications

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Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.

| To Appear | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2007 |

To Appear









  • Luo C. (2017) On Channel State Feedback Model and Overhead in Theoretical and Practical Views, DOI:10.48550/arxiv.1705.05369.
  • Klasing R, Hsieh SY, Luo C. (2017) Message from I-SPAN 2017 Program Chairs, Proceedings - 14th International Symposium on Pervasive Systems, Algorithms and Networks, I-SPAN 2017, 11th International Conference on Frontier of Computer Science and Technology, FCST 2017 and 3rd International Symposium of Creative Computing, ISCC 2017, volume 2017-November, pages xv-xvi, DOI:10.1109/ISPAN-FCST-ISCC.2017.97.
  • Zhang H, Luo C, Wang Q, Kitchin M, Parmley A, Monge-Alvarez J, Casaseca-de-la-Higuera P. (2017) A Novel Infrared Video Surveillance System Using Deep Learning Based Techniques, Multimedia Tools and Applications.
  • Ren P, Sun W, Luo C, Hussain A. (2017) Clustering-Oriented Multiple Convolutional Neural Networks for Single Image Super-Resolution, Cognitive Computation, volume 10, no. 1, pages 165-178, DOI:10.1007/s12559-017-9512-2. [PDF]
  • Yang R, Luo C. (2017) High Speed Wireless USB for Internet of Things, The 14th International Symposium on Pervasive Systems, Algorithms, and Networks, Exeter, Uk, 21st - 23rd Jun 2017.
  • Zhang H, Luo C, Yu X, Ren P. (2017) MCMC based Generative Adversarial Networks for Handwritten Numeral Augmentation, The 6th International Conference on Communications, Signal Processing, and Systems (CSPS), Harbin, China, 14th - 16th Jul 2017.
  • Ullah H, Abu-Tair M, McClean S, P N, Parr G, Luo C. (2017) An Unmanned Aerial Vehicle Based Wireless Network for Bridging Communication, The 14th International Symposium on Pervasive Systems, Algorithms, and Networks, Exeter, 21st - 23rd Jun 2017.
  • Ullah H, McClean S, Nixon P, Parr G, Luo C. (2017) An Optimal UAV Deployment Algorithm for Bridging Communication, 15th International Conference on ITS Telecommunications (ITST), 2017, Warsaw, Poland, 29th May - 31st Aug 2017, DOI:10.1109/ITST.2017.7972194.
  • Beduschi A, Cinnamon J, Langford J, Luo C, Owen D. (2017) Building Digital Identities: The Challenges, Risks and Opportunities of Collecting Behavioural Attributes for new Digital Identity Systems, University of Exeter and Coelition, 40 pages.
  • Yu X, Wu X, Luo C, Ren P. (2017) Deep learning in remote sensing scene classification: a data augmentation enhanced convolutional neural network framework, GIScience and Remote Sensing, volume 54, no. 5, pages 741-758, DOI:10.1080/15481603.2017.1323377.




  • Martinez D, Casaseca P, Fernandez M, Amira A, Grecos C, Lopez C, Luo C. (2014) A Stochastic Modelling Framework for the Reconstruction of Cardiovascular Signals, IEEE Engineering in Medicine and Biology Society, Chicago, 26th - 30th Aug 2014.
  • Luo C, Casaseca P, McClean S, Parr G, Grecos C. (2014) Analysis of Coloured Noise in Received Signal Strength Using the Allan Variance, EUSIPCO, Lisbon, 7th - 11th Sep 2014.
  • Di M, Song H, Ren P, Luo C. (2014) Elongated Strip Oil Spill Segmentation Based on A Cooperative Model, 28th - 29th Sep 2014.
  • Amira A, Ramzan N, Grecos C, Wang Q, Pervez Z, Wang X, Luo C. (2014) A Reconfigurable Supporting Connected Health Environment for People with Chronic Diseases, Healthcare Informatics and Analytics Emerging Issues and Trends, Medical Info Science Reference.
  • Luo C, McClean SI, Parr G, Wang Q, Wang X, Grecos C. (2014) A Communication Model to Decouple the Path Planning and Connectivity Optimization and Support Cooperative Sensing, IEEE Transactions on Vehicular Technology, volume 63, no. 8, pages 3985-3997, DOI:10.1109/tvt.2014.2305474. [PDF]
  • Patterson T, McClean S, Morrow P, Parr G, Luo C. (2014) Timely autonomous identification of UAV safe landing zones, Image and Vision Computing, volume 32, no. 9, pages 568-578, DOI:10.1016/j.imavis.2014.06.006. [PDF]


  • Khan K, Wang Q, Grecos C, Luo C, Wang X. (2013) MeshCloud: Integrated Cloudlet and Wireless Mesh Network for Real-Time Applications, Proc. 20th IEEE International Conference on Electronics, Circuits, and Systems, Abu Dhabi, Uae, 8th - 11th Dec 2013.
  • Luo C, Wang Q, Wang X, Grecos C, Yang R, Ren P. (2013) Exploiting selection diversity and recovering spectrum loss in Wireless Sensor Networks with directional antennas, Globecom, 2013 IEEE, Atlanta, Georgia, 9th - 13th Dec 2013.
  • Luo C, McClean SI, Parr G, Teacy L, De Nardi R. (2013) UAV Position Estimation and Collision Avoidance Using the Extended Kalman Filter, IEEE Transactions on Vehicular Technology, volume 62, no. 6, pages 2749-2762, DOI:10.1109/tvt.2013.2243480. [PDF]
  • Luo C, Gong Y, McClean S, Ren P, Parr G. (2013) Multiple-source multiple-destinations relay channels with network coding, IET Communications, volume 7, no. 17, pages 1958-1968, DOI:10.1049/iet-com.2012.0828.
  • Nightingale J, Wang Q, Wang R, Luo C, Ramzan N, Grecos C, Wang X, Amira A. (2013) Mobile Video Cloud Networks, Mobile Networks and Cloud Computing Convergence for Progressive Services and Applications, IGI Global.


  • Luo C, Ward P, Cameron S, Parr G, McClean S. (2012) Communication provision for a team of remotely searching UAVs: A mobile relay approach, IEEE Globecom, Anaheim, California, 3rd - 7th Dec 2012.
  • Yu Gong, Chunbo Luo, Zhi Chen. (2012) Two-Path Succussive Relaying With Hybrid Demodulate and Forward, IEEE Transactions on Vehicular Technology, volume 61, no. 5, pages 2044-2053, DOI:10.1109/tvt.2012.2191807. [PDF]




  • Luo C, Gong Y, Fuchun Z. (2009) Full Interference Cancellation for Two-Path Cooperative Communications, Wireless Communications and Networking Conference, 2009. WCNC 2009. IEEE, Budapest, Hungary, 5th - 8th Apr 2009.
  • Luo C, Abu-Salem K, Gong Y. (2009) A New Strategy for the Blind MMSE Equalization, 17th European Signal Processing Conference 2009, Glasgow, Uk, 24th - 28th Aug 2009.


  • Luo C, Gong Y, Gong Y, Li S. (2007) A New Blind Equalization Algorithm Based on Convex Combination, Communications, Circuits and Systems, 2007. ICCCAS 2007. International Conference on, Kokura, Japan, 11th - 13th Jul 2007.

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Further information

Student projects

Project ideas:

  1. Machine learning on UAV data for events classification. 
  2. A web application with machine learning models to process user input disaster images.
  3. A web system with database management for UAV visual data publication and update. 
  4. A crawler system for images collected by UAVs on disasters (to automatically retrieve data from social networks and websites about disasters such as flood, landslides etc.).

Research Datasets


VisualWind is a novel video dataset including: 6000 labeled video clips, covering eleven wind classes of the Beaufort scale. The videos are collected from social media, public cameras, and self-recording. Every video clip has a fixed 10-second length with varied frame rates, and contains scenes of various trees swaying in different scales of wind.

Data access: email to for the link and code. 

Example videoframes:

Benchmark results:

Paper to cite: Qin Zhang, Jialang Xu, Matthew Crane, Chunbo Luo, See the wind: Wind scale estimation with optical flow and VisualWind dataset, Science of The Total Environment, Volume 846, 2022, 157204.


2. SWED: Sentinel-2 Water Edges Dataset

We present the Sentinel-2 Water Edges Dataset (SWED), a new and bespoke labelled image dataset for the development and bench-marking of techniques for the automated extraction of coastline morphology data from Sentinel-2 images. Composed of 16 labelled training Sentinel-2 scenes, and 98 test label-image pairs, SWED is globally distributed and contains examples of many different coastline types and natural and anthropogenic coastline features.

Dataset access: The Sentinel-2 Water Edges Dataset can be obtained by visiting and used under the Geospatial Commission Data Exploration license.

Paper to cite: Seale C, Redfern T, Chatfield P, Luo C, Dempsey K. (2022) Coastline detection in satellite imagery: A deep learning approach on new benchmark dataRemote Sensing of Environment, volume 278, article no. 113044, DOI:10.1016/j.rse.2022.113044. [PDF

3. UAV Visual image of disasters

To be published soon. 

AI/ML models with code/data

1. Wind scale estimation using deep learning models (CNN, LSTM) - 2022


2. Industry IoT security (intrusion detection) using federated learning - 2023


3. Coastal detection from Sentinel 2 data and deep U-net - 2022


4. Cloud center resource optimisation using Reinforcement learning - 2022



For archive only. 
  • Many thanks IDSAI for providing seedcorn support to the project on machine learning methods for Greenland  ice sheet radar data processing led by Steven Palmer and Chunbo, working with Charlie Kirkwood.
  • A funded PhD project: Monitoring of landslide hazards with wireless sensor networks and machine learning, supervised by Dr Georgie Bennett, Dr Kyle Roskilly, and Dr Chunbo Luo, click to apply
  • A funded PhD project: Machine learning for geospatial intelligence, supervised by Dr Isabel Sargent, Ordnance Survey and Dr Chunbo Luo click to apply
  • A funded PhD project: Detecting the impacts of river plumes in coastal waters from satellite imagery using machine learning, NERC GW4+ DTP PhD studentship for 2023 Entry.
  • Congratulations to our new successful grant: Optimising Energy Demand in Rural Communities via Precision Agriculture Technology (SWIFT), led by LENKÉ: Space & Water Solutions Ltd
  • Our special issue is accepting paper now: Prediction and (Back)Tracking of Marine Oil Spill Drift and Diffusion, in the journal Frontiers in Marine Science. Link
  • We are delighted to report one KTP project will be funded by UKRI (2-year postdoc job - click to apply)
  • Congratulations to Jiawei, Peigeng, Zhipeng for receiving the CSC-Exeter PhD project grants!  
  • Our IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Special Issue: Cooperative Perception for Computer Vision in Remote SensingClick to submit your work NOW for early review and publication!
  • Our new MSc Data Science (Apprenticeship) programme is recruiting (Submit your application).

Selected papers

Selected themed papers mostly from last 5 years: 

1. Machine learning for remote sensing & environment observation

  1. Zhipeng Liu, Chunbo Luo, Geyong Min, Zishu Liu and Zhuhui Li, DisasterScope: A Comprehensive Dataset and RTMDet-Based Methodology for Object Detection in Disaster-Related Remote Sensing Images. IEEE International Geoscience and Remote Sensing Symposium, 2024.

  2. Zhang Q, Xu J, Crane M, Luo C. (2022) See the wind: Wind scale estimation with optical flow and VisualWind dataset, Science of The Total Environment, volume 846, DOI:10.1016/j.scitotenv.2022.157204. (IF: 10.2) 

  3. Seale C, Redfern T, Chatfield P, Luo C, Dempsey K. (2022) Coastline detection in satellite imagery: A deep learning approach on new benchmark data, Remote Sensing of Environment, volume 278, article no. 113044, DOI:10.1016/j.rse.2022.113044. (IF: 13.9) 

  4. Xu J, Luo C, Chen X, Wei S, and Luo Y.(2020) "Remote Sensing Change Detection Based on Multidirectional Adaptive Feature Fusion and Perceptual Similarity" Remote Sensing, vol. 13, no. 15, pp. 3053.

  5. Yu X, Zhang H, Luo C, Qi H and Ren P. (2018) "Oil Spill Segmentation via Adversarial f-Divergence Learning," IEEE Transactions on Geoscience and Remote Sensing. doi: 10.1109/TGRS.2018.2803038 

  6. Yu X, Wu X, Luo C, Ren P. (2017) Deep learning in remote sensing scene classification: a data augmentation enhanced convolutional neural network framework, GIScience and Remote Sensing, volume 54, no. 5, pages 741-758, DOI:10.1080/15481603.2017.1323377. (Currently the 2nd highest cited paper in this journal)

  7. Ren P, Di M, Song H, Luo C, Grecos C. (2016) Dual Smoothing for Marine Oil Spill Segmentation, IEEE Geoscience and Remote Sensing Letters, volume 13, no. 1, pages 82-86, DOI:10.1109/LGRS.2015.2497716. 


2. Smart Sensors for landslide and movement detection

  1. Newby, Kate, Georgina Bennett, Kyle Roskilly, Alessandro Sgarabotto, Chunbo Luo, and Irene Manzella. Smart boulders for real-time detection of hazardous movement on landslides. No. EGU24-394. Copernicus Meetings, 2024.

  2. Sgarabotto A, Manzella I, Roskilly K, Clark MJ, Bennett GL, Luo C, Franco AM. Evaluating the use of smart sensors in ground-based monitoring of landslide movement with laboratory experiments. EGUsphere. 2023 Nov 27;2023:1-30.

  3. Sgarabotto A, Majtan E, Manzella I, Raby A, Fourtakas G, Rogers BD, Roskilly K, Panici D, Bennett GL, Franco CL, Aldina MA. Using Smart Sensors to Track Woody Debris in Flume Experiments. InProceedings of the 40th IAHR World Congress 2023 Aug 25.

  4. Sgarabotto A, Manzella I, Raby A, Roskilly K, Egedusevic M, Panici D, Clark M, Boulton SJ, Franco A, Bennett GL, Luo C. Smart sensors to detect movements of cobbles and large woody debris dams. Insights from lab experiments. InEGU General Assembly Conference Abstracts 2023 May (pp. EGU-16276).

  5. Roskilly, Kyle, Georgina Bennett, Miles Clark, Aldina Franco, Martina Egedusevic, Robin Curtis, Joshua Jones, Michael Whitworth, Chunbo Luo, and Irene Manzella. "Smart cobbles and boulders for monitoring movement in rivers and on hillslopes." In EGU General Assembly Conference Abstracts, pp. EGU-14870. 2023.

  6. Sgarabotto, Alessandro, Irene Manzella, Kyle Roskilly, Chunbo Luo, Miles Clark, Aldina Franco, Georgina L. Bennett, and Alison Raby. "Investigating boulder motions with smart sensors in lab experiments." In EGU General Assembly Conference Abstracts, pp. EGU22-10198. 2022.

  7. Roskilly, Kyle, Georgina Bennett, Robin Curtis, Martina Egedusevic, Joshua Jones, Michael Whitworth, Benedetta Dini, Chunbo Luo, Irene Manzella, and Aldina Franco. "SENSUM project, Smart SENSing of landscapes Undergoing hazardous hydrogeomorphic Movement." In EGU General Assembly Conference Abstracts, pp. EGU22-10289. 2022.

  8. Y. Mi, C. Luo, G. Min, W. Miao, L. Wu and T. Zhao, "Sensor-Assisted Global Motion Estimation for Efficient UAV Video Coding," ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK, 2019, pp. 2237-2241, doi: 10.1109/ICASSP.2019.8682798.

3. Intelligent networks for sensing equipement and vehicles

  1. Li Z, Min G, Ren P, Luo C, Zhao L, Luo C. (2024) Ubiquitous and Robust UxV Networks: Overviews, Solutions, Challenges, and OpportunitiesIEEE Network, pages 1-1, DOI:10.1109/mnet.2024.3352691

  2. Wu Y, Fang X, Luo C, Min G. Intelligent Content Pre-caching Scheme for Platoon-based Edge Vehicular NetworksIEEE Internet of Things Journal, pages 1-1, DOI:10.1109/jiot.2022.3178099. 

  3. Herberth R, Menz L, Korper S, Luo C, Gauterin F, Gerlicher A, Wang Q. Identifying Atypical Travel Patterns for Improved Medium-Term Mobility Prediction, IEEE Transactions on Intelligent Transportation Systems, pages 1-12, DOI:10.1109/tits.2019.2947347. 

  4. Li Z, Zhao L, Min G, Al-Dubai AY, Hawbani A, Zomaya AY, Luo C. (2023) Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method, IEEE Transactions on Intelligent Transportation Systems, volume 24, no. 12, pages 14022-14036, DOI:10.1109/TITS.2023.3300082. 

  5. Zhang J, Luo C, Carpenter M, Min G. (2022) Federated Learning for Distributed IIoT Intrusion Detection Using Transfer ApproachesIEEE Transactions on Industrial Informatics, volume 19, no. 7, pages 8159-8169, DOI:10.1109/tii.2022.3216575. 

  6. Wu J, Luo C, Luo Y, Li K. (2022) Distributed UAV Swarm Formation and Collision Avoidance Strategies Over Fixed and Switching TopologiesIEEE Trans Cybern, volume 52, no. 10, pages 10969-10979, DOI:10.1109/TCYB.2021.3132587. 

  7. Chen Z, Hu J, Min G, Luo C, El-Ghazawi T. (2021) Adaptive and Efficient Resource Allocation in Cloud Datacenters Using Actor-Critic Deep Reinforcement LearningIEEE Transactions on Parallel and Distributed Systems, DOI:10.1109/TPDS.2021.3132422. 

  8. Miao W, Luo C, Min G, Mi Y, Wang H. (2021) Unlocking the Potential of 5G and beyond Networks to Support Massive Access of Ground and Air Devices, IEEE Transactions on Network Science and Engineering, volume 8, no. 4, pages 2825-2836, DOI:10.1109/TNSE.2021.3051294. 

  9. Miao W, Luo C, Min G, Mi Y, Yu Z. (2021) Location-Based Robust Beamforming Design for Cellular-Enabled UAV CommunicationsIEEE Internet of Things Journal, volume 8, no. 12, pages 9934-9944, DOI:10.1109/jiot.2020.3028853.

  10. Miao W, Luo C, Min G, Zhao Z. (2020) Lightweight 3-D Beamforming Design in 5G UAV Broadcasting CommunicationsIEEE Transactions on Broadcasting, volume 66, no. 2, pages 515-524, DOI:10.1109/TBC.2020.2990564. 

  11. Zhan W, Luo C, Min G, Wang C, Zhu Q, Duan H. (2020) Mobility-Aware Multi-User Offloading Optimization for Mobile Edge ComputingIEEE Transactions on Vehicular Technology, volume 69, no. 3, pages 3341-3356, DOI:10.1109/tvt.2020.2966500. [PDF

  12. Khan AH, Cao X, Li S, Luo C. (2020) Using Social Behavior of Beetles to Establish a Computational Model for Operational ManagementIEEE Transactions on Computational Social Systems, volume 7, no. 2, pages 492-502, DOI:10.1109/tcss.2019.2958522. [PDF



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