Yuxu Lu

Orcid: 0000-0001-9845-7516

According to our database1, Yuxu Lu authored at least 28 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
AiOENet: All-in-One Low-Visibility Enhancement to Improve Visual Perception for Intelligent Marine Vehicles Under Severe Weather Conditions.
IEEE Trans. Intell. Veh., February, 2024

Blind Image Despeckling Using a Multiscale Attention-Guided Neural Network.
IEEE Trans. Artif. Intell., January, 2024

MvKSR: Multi-View Knowledge-Guided Scene Recovery for Hazy and Rainy Degradation.
IEEE Trans. Instrum. Meas., 2024

AoSRNet: All-in-One Scene Recovery Networks via multi-knowledge integration.
Knowl. Based Syst., 2024

Real-Time Multi-Scene Visibility Enhancement for Promoting Navigational Safety of Vessels Under Complex Weather Conditions.
CoRR, 2024

OneRestore: A Universal Restoration Framework for Composite Degradation.
CoRR, 2024

S3Net: Semi-self-supervised neural network for visibility enhancement of speckled images.
Comput. Electr. Eng., 2024

Attention-oriented residual block for real-time low-light image enhancement in smart ports.
Comput. Electr. Eng., 2024

2023
Haze Visibility Enhancement for Promoting Traffic Situational Awareness in Vision-Enabled Intelligent Transportation.
IEEE Trans. Veh. Technol., December, 2023

Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways.
IEEE Trans. Intell. Transp. Syst., November, 2023

MDSFE: Multiscale Deep Stacking Fusion Enhancer Network for Visual Data Enhancement.
IEEE Trans. Instrum. Meas., 2023

Let You See in Haze and Sandstorm: Two-in-One Low-Visibility Enhancement Network.
IEEE Trans. Instrum. Meas., 2023

GradDT: Gradient-Guided Despeckling Transformer for Industrial Imaging Sensors.
IEEE Trans. Ind. Informatics, 2023

Deep Network-Enabled Haze Visibility Enhancement for Visual IoT-Driven Intelligent Transportation Systems.
IEEE Trans. Ind. Informatics, 2023

SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023


2022
MTRBNet: Multi-Branch Topology Residual Block-Based Network for Low-Light Enhancement.
IEEE Signal Process. Lett., 2022

Low-Light Image Enhancement via Gradient Prior-Aided Network.
IEEE Access, 2022

Intelligent Maritime Surveillance Framework Driven by Fusion of Camera-Based Vessel Detection and AIS Data.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Fast Deep Multi-patch Progressive Network for Low-light Image Enhancement in Intelligent Transportation Systems.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Rep-Enhancer: Re-parameterizing Neural Network for Real-time Low-light Enhancement in Visual Maritime Surveillance.
Proceedings of the 20th IEEE International Conference on Embedded and Ubiquitous Computing, 2022

2021
Towards Low-Visibility Enhancement in Maritime Video Surveillance: An Efficient and Effective Multi-Deep Neural Network.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

Heterogeneous Twin Dehazing Network for Visibility Enhancement in Maritime Video Surveillance.
Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference, 2021

2020
Low-Light Maritime Image Enhancement with Regularized Illumination Optimization and Deep Noise Suppression.
CoRR, 2020

Low-Light Image Enhancement With Regularized Illumination Optimization and Deep Noise Suppression.
IEEE Access, 2020

DSPNet: Deep Learning-Enabled Blind Reduction of Speckle Noise.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Low-light Image Enhancement with Deep Blind Denoising.
Proceedings of the ICMLC 2020: 2020 12th International Conference on Machine Learning and Computing, 2020

2019
Learning a Deep Convolutional Network for Speckle Noise Reduction in Underwater Sonar Images.
Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019


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