Yurong Guo

Orcid: 0000-0001-9974-6985

Affiliations:
  • North China Electric Power University, Department of Electronic and Communication Engineering, China
  • Beijing University of Posts and Telecommunications, China (PhD 2024)


According to our database1, Yurong Guo authored at least 14 papers between 2019 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
A Segmentation-Driven Editing Method for Bolt Defect Augmentation and Detection.
IEEE Trans. Syst. Man Cybern. Syst., May, 2026

2025
Understanding Episode Hardness in Few-Shot Learning.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2025

A decoupled scene-equipment fusion method for power substation equipment detection.
Knowl. Based Syst., 2025

2024
TL-CLIP: A Power-specific Multimodal Pre-trained Visual Foundation Model for Transmission Line Defect Recognition.
CoRR, 2024

2023
Focus the Overlapping Problem on Few-Shot Object Detection via Multiple Predictions.
Proceedings of the Pattern Recognition and Computer Vision - 6th Chinese Conference, 2023

Task-aware Adaptive Learning for Cross-domain Few-shot Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Learning Calibrated Class Centers for Few-Shot Classification by Pair-Wise Similarity.
IEEE Trans. Image Process., 2022

2021
Competing ratio loss for discriminative multi-class image classification.
Neurocomputing, 2021

ATRM: Attention-based Task-level Relation Module for GNN-based Few-shot Learning.
CoRR, 2021

TLRM: Task-level Relation Module for GNN-based Few-Shot Learning.
Proceedings of the International Conference on Visual Communications and Image Processing, 2021

2019
IMS-SSH: multiscale face detection method in unconstrained settings.
J. Electronic Imaging, 2019

Multiple Feature Reweight DenseNet for Image Classification.
IEEE Access, 2019

Competing Ratio Loss for Multi-class image Classification.
Proceedings of the 2019 IEEE Visual Communications and Image Processing, 2019

Channel-Wise and Feature-Points Reweights Densenet for Image Classification.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019


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