Rongguang Ye

Orcid: 0000-0002-7759-1254

According to our database1, Rongguang Ye authored at least 15 papers between 2020 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization.
CoRR, 2024

pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving.
CoRR, 2024

PraFFL: A Preference-Aware Scheme in Fair Federated Learning.
CoRR, 2024

Data-Driven Preference Sampling for Pareto Front Learning.
CoRR, 2024

Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems.
CoRR, 2024

Evolutionary Preference Sampling for Pareto Set Learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2024

2023
Localization Distillation for Object Detection.
IEEE Trans. Pattern Anal. Mach. Intell., August, 2023

LiCAM: Long-Tailed Instance Segmentation with Real-Time Classification Accuracy Monitoring.
J. Circuits Syst. Comput., January, 2023

2022
Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation.
IEEE Trans. Cybern., 2022

A Generative Adversarial Network Based Motion Planning Framework for Mobile Robots in Dynamic Human-Robot Integration Environments.
Proceedings of the Social Robotics - 14th International Conference, 2022

SIA-Unet: A Unet with Sequence Information for Gastrointestinal Tract Segmentation.
Proceedings of the PRICAI 2022: Trends in Artificial Intelligence, 2022

Localization Distillation for Dense Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Localization Distillation for Object Detection.
CoRR, 2021

A Natural Language Instruction Disambiguation Method for Robot Grasping.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2021

2020
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020


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