Wenzhong Shen

Orcid: 0000-0002-9029-4940

According to our database1, Wenzhong Shen authored at least 14 papers between 2006 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
UAV Cross-Domain Detection in IoT-Enabled Environments via Class-Aware Correlation-Controlled Feature Learning.
IEEE Internet Things J., 2026

2025
Exploring the effectiveness of cell size criteria and comparison of nine recently developed metaheuristic algorithms for wind farm layout optimization.
J. Supercomput., November, 2025

LCNet-ViT-FG: a product recognition method based on the fusion of self-supervised pretrained CNN and transformer.
J. Electronic Imaging, 2025

2024
OpenFE: feature-extended OpenMax for open set facial expression recognition.
Signal Image Video Process., 2024

Generative network copyright protection method based on iris information watermarking.
J. Electronic Imaging, 2024

End-to-end multibranch network for palm vein recognition and liveness detection.
J. Electronic Imaging, 2024

End-to-end multitasking network for smart container product positioning and segmentation.
J. Electronic Imaging, 2024

2023
FOF: a fine-grained object detection and feature extraction end-to-end network.
Int. J. Multim. Inf. Retr., December, 2023

Pixel-level self-paced adversarial network with multiple attention in single image super-resolution.
Signal Image Video Process., July, 2023

IrisMarkNet: Iris feature watermarking embedding and extraction network for image copyright protection.
Appl. Intell., May, 2023

IrisST-Net for iris segmentation and contour parameters extraction.
Appl. Intell., May, 2023

A Pairwise DomMix Attentive Adversarial Network for Unsupervised Domain Adaptive Object Detection.
IEEE Signal Process. Lett., 2023

2021
Is normalized iris optimal for iris recognition based on deep learning?
J. Electronic Imaging, 2021

2006
Dynamic information system and its rough set model based on time sequence.
Proceedings of the 2006 IEEE International Conference on Granular Computing, 2006


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