Mr Lu Yuxu

PhD Student

Lu Yuxu received his both Bachelor’s Degrees and Master’s Degree from Wuhan University of Technology. He is currently pursuing his PhD under the supervision of Dr Yang Dong.

yuxulouis.lu@connect.polyu.hk
Maritime, Aviation and Transport Studies, Intelligent Transportation, Intelligent Maritime, Computer Vision, Machine Learning
Personal Website

Education and Academic Qualifications

Bachelor of Engineering, Wuhan University of Technology, 2020
Master of Engineering, Wuhan University of Technology, 2023

Research Outputs

Journal Publications

Lu, Y., Guo, Y., Liu, R. W., Chui, K. T., & Gupta, B. B. (2022). Graddt: Gradient-guided despeckling transformer for industrial imaging sensors. IEEE Transactions on Industrial Informatics, 19(2), 2238-2248.
Lu, Y., Guo, Y., Liu, R. W., & Ren, W. (2022). MTRBNet: Multi-branch topology residual block-based network for low-light enhancement. IEEE Signal Processing Letters, 29, 1127-1131.
Lu, Y., Guo, Y., & Liang, M. (2021). CNN-enabled visibility enhancement framework for vessel detection under haze environment. Journal of advanced transportation, 2021, 1-14.
Lu, Y., Gao, Y., Guo, Y., Xu, W., & Hu, X. (2022). Low-light image enhancement via gradient prior-aided network. IEEE Access, 10, 92583-92596.
Guo, Y., Lu, Y., Liu, R. W., & Zhu, F. (2023). Blind Image Despeckling Using Multi-Scale Attention-Guided Neural Network. IEEE Transactions on Artificial Intelligence. (co-first author)
Guo, Y., Lu, Y., Qu, J., Liu, R. W., & Ren, W. (2022). MDSFE: Multiscale Deep Stacking Fusion Enhancer Network for Visual Data Enhancement. IEEE Transactions on Instrumentation and Measurement, 72, 1-12. (co-first author)
Guo, Y., Lu, Y., & Liu, R. W. (2022). Lightweight deep network-enabled real-time low-visibility enhancement for promoting vessel detection in maritime video surveillance. The Journal of Navigation, 75(1), 230-250. (co-first author)
Guo, Y., Lu, Y., Liu, R. W., Yang, M., & Chui, K. T. (2020). Low-light image enhancement with regularized illumination optimization and deep noise suppression. IEEE Access, 8, 145297-14531. (co-first author)
Gao, Y., Xu, W., & Lu, Y. (2023). Let You See in Haze and Sandstorm: Two-in-One Low-visibility Enhancement Network. IEEE Transactions on Instrumentation and Measurement. (Corresponding author)
Liu, R. W., Yuan, W., Chen, X., & Lu, Y. (2021). An enhanced CNN-enabled learning method for promoting ship detection in maritime surveillance system. Ocean Engineering, 235, 109435. (Corresponding author)
Qu, J., Gao, Y., Lu, Y., Xu, W., & Liu, R. W. (2023). Deep learning-driven surveillance quality enhancement for maritime management promotion under low-visibility weathers. Ocean & Coastal Management, 235, 106478. (Corresponding author)
Guo, Y., Liu, R. W., Lu, Y., Nie, J., Lyu, L., Xiong, Z., ... & Niyato, D. (2023). Haze visibility enhancement for promoting traffic situational awareness in vision-enabled intelligent transportation. IEEE Transactions on Vehicular Technology.
Guo, Y., Liu, R. W., Qu, J., Lu, Y., Zhu, F., & Lv, Y. (2023). Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways. IEEE Transactions on Intelligent Transportation Systems.
Qu, J., Liu, R. W., Guo, Y., Lu, Y., Su, J., & Li, P. (2023). Improving maritime traffic surveillance in inland waterways using the robust fusion of AIS and visual data. Ocean Engineering, 275, 114198.
Liu, R. W., Guo, Y., Lu, Y., Chui, K. T., & Gupta, B. B. (2022). Deep network-enabled haze visibility enhancement for visual IoT-driven intelligent transportation systems. IEEE Transactions on Industrial Informatics, 19(2), 1581-1591.
Guo, Y., Lu, Y., Guo, Y., Liu, R. W., & Chui, K. T. (2021). Intelligent vision-enabled detection of water-surface targets for video surveillance in maritime transportation. Journal of advanced transportation, 2021, 1-14.