Outputs (34)

Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets (2024)
Journal Article
Gao, H., Huang, B., Chen, G., Xia, L., & Radenkovic, M. (2024). Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets. Remote Sensing of Environment, 315, Article 114425. https://doi.org/10.1016/j.rse.2024.114425

The world’s first scientific satellite for sustainable development goals (SDGSAT-1) provides valuable data about offshore small-scale ocean phenomena, including the Kármán vortex street phenomenon. Although the simulation of the oce... Read More about Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets.

Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima (2024)
Journal Article
Yu, Y., Huang, B., Radenkovic, M., Wang, T., & Chen, G. (2024). Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima. IEEE Transactions on Geoscience and Remote Sensing, 62, Article 4211013. https://doi.org/10.1109/tgrs.2024.3464850

Subsurface chlorophyll maximum (SCM) is a crucial ecological indicator for marine ecosystems. Previous studies have indicated that this phenomenon is globally widespread. Although the biogeochemical argo assimilation results have yielded positive res... Read More about Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima.

ARU2-Net: A Deep Learning Approach for Global-Scale Oceanic Eddy Detection (2024)
Journal Article
Geng, J., Gao, H., Huang, B., Radenkovic, M., & Chen, G. (2024). ARU2-Net: A Deep Learning Approach for Global-Scale Oceanic Eddy Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 11997-12007. https://doi.org/10.1109/jstars.2024.3419175

Ocean eddies have a significant impact on marine ecosystems and the climate because they transport essential substances in the ocean. Detection of ocean eddies has become one of the most active topics in physical ocean research. In recent years, rese... Read More about ARU2-Net: A Deep Learning Approach for Global-Scale Oceanic Eddy Detection.

Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network (2024)
Journal Article
Zhang, X., Huang, B., Chen, G., Ge, L., Radenkovic, M., & Hou, G. (2024). Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network. IEEE Transactions on Geoscience and Remote Sensing, 62, Article 4205214. https://doi.org/10.1109/tgrs.2024.3388040

Efficient eddy trajectory prediction driven by multiinformation fusion can facilitate the scientific research of oceanography, while the complicated dynamics mechanism makes this issue challenging. Benefiting from ocean observing technology, the eddy... Read More about Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network.

Instant deep sea debris detection for maneuverable underwater machines to build sustainable ocean using deep neural network (2023)
Journal Article
Huang, B., Chen, G., Zhang, H., Hou, G., & Radenkovic, M. (2023). Instant deep sea debris detection for maneuverable underwater machines to build sustainable ocean using deep neural network. Science of the Total Environment, 878, Article 162826. https://doi.org/10.1016/j.scitotenv.2023.162826

Deep sea debris is any persistent man-made material that ends up in the deep sea. The scale and rapidly increasing amount of sea debris are endangering the health of the ocean. So, many marine communities are struggling for the objective of a clean,... Read More about Instant deep sea debris detection for maneuverable underwater machines to build sustainable ocean using deep neural network.

Oceanic Eddy Identification Using Pyramid Split Attention U-Net With Remote Sensing Imagery (2023)
Journal Article
Zhao, N., Huang, B., Yang, J., Radenkovic, M., & Chen, G. (2023). Oceanic Eddy Identification Using Pyramid Split Attention U-Net With Remote Sensing Imagery. IEEE Geoscience and Remote Sensing Letters, 20, Article 1500605. https://doi.org/10.1109/lgrs.2023.3243902

Oceanic eddy is the ubiquitous ocean flow phenomenon, which has been the key factor in the transportation of ocean energy and materials. Consequently, oceanographic understanding can be enhanced by the intelligent identification of eddy. State-of-the... Read More about Oceanic Eddy Identification Using Pyramid Split Attention U-Net With Remote Sensing Imagery.

Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles (2022)
Journal Article
Brocklehurst, C., & Radenkovic, M. (2022). Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles. Journal of Sensor and Actuator Networks, 11(3), Article 35. https://doi.org/10.3390/jsan11030035

The increased interest in autonomous vehicles has led to the development of novel networking protocols in VANETS. In such a widespread safety critical application, security is paramount to the implementation of the networks. We view new autonomous ve... Read More about Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles.

Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles (2022)
Data
Brocklehurst, C., & Radenkovic, M. (2022). Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles. [Dataset]. https://doi.org/10.3390/jsan11030035

The increased interest in autonomous vehicles has led to the development of novel networking protocols in VANETs In such a widespread safety-critical application, security is paramount to the implementation of the networks. We view new autonomous veh... Read More about Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles.

Exploring user behavioral data for adaptive cybersecurity (2019)
Journal Article
Addae, J. H., Sun, X., Towey, D., & Radenkovic, M. (2019). Exploring user behavioral data for adaptive cybersecurity. User Modeling and User-Adapted Interaction, 29(3), 701-750. https://doi.org/10.1007/s11257-019-09236-5

This paper describes an exploratory investigation into the feasibility of predictive analytics of user behavioral data as a possible aid in developing effective user models for adaptive cybersecurity. Partial least squares structural equation modelin... Read More about Exploring user behavioral data for adaptive cybersecurity.

CognitiveCharge: disconnection tolerant adaptive collaborative and predictive vehicular charging (2018)
Presentation / Conference Contribution
Radenkovic, M., & Walker, A. (2018). CognitiveCharge: disconnection tolerant adaptive collaborative and predictive vehicular charging.

Electric vehicles (EVs) are rapidly becoming more common and ownership is set to rise globally in coming years. The potential impacts of increased EVs on the electrical grid have been widely investigated and in its current state, existing grid infras... Read More about CognitiveCharge: disconnection tolerant adaptive collaborative and predictive vehicular charging.