Ye YUAN (袁野)

Ye YUAN (袁野)

Northeast Forestry University (NEFU)

I am a Associate Professor in the College of Computer and Control Engineering, Northeast Forestry University, where I worked on deep learning-based image processing methods and vision applications for remote sensing. I received my Ph.D. from College of Computer Science and Technology, Harbin Engineering University, China in December 2023, advised by Prof. Wu Yanxia. Before that, I received my B.S. from College of Computer Science and Technology, Harbin Engineering University in June 2017.

🔥 News

  • 2024.12:  🎉🎉 New stage of career! I joined the College of Computer and Control Engineering at Northeast Forestry University!
  • 2024.10:  🎉🎉 One journal paper about oriented remote sensing object detection has been accepted by IEEE JSTARS (link)!
  • 2024.04:  🎉🎉 One conference paper about unpaired image despeckling has been accepted by IEEE ICME 2024 (link)!
  • 2024.04:  🎉🎉 One conference paper about adversarial attack for SAM has been accepted by IEEE ICME 2024 (link)!
  • 2023.12:  🎉🎉 Completed the defense of my PhD thesis (Research on deep learning based denoising methods for SAR images) and received my PhD degree!
  • 2023.09:  🎉🎉 One journal paper about self-supervised SAR image denoising has been accepted by IEEE TGRS (link)!

📖 Experience

  • 2024.12 - now, Associate Professor, College of Computer and Control Engineering, Northeast Forestry University

  • 2018.09 - 2023.12, Ph.D, College of Computer Science and Technology, Harbin Engineering University
  • 2017.09 - 2018.06, M.S. transfer to Ph.D, College of Computer Science and Technology, Harbin Engineering University
  • 2013.09 - 2017.06, B.S., College of Computer Science and Technology, Harbin Engineering University

📝 Research Spotlight

IEEE TGRS 2023
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Segmentation-Guided Semantic-Aware Self-Supervised Denoising for SAR Image

Ye Yuan, Yanxia Wu*, Pengming Feng, Yan Fu, Yulei Wu

  • We propose a segmentation-guided semantic-aware self-supervised denoising method for SAR images, namely, SARDeSeg, where a segmentation network is incorporated with a denoising network and guides it to learn and be aware of the semantic information of the input noisy SAR images. The proposed SARDeSeg outperforms state-of-the-art (SOTA) denoising methods for SAR images, particularly in preserving detailed edge features.
IEEE ICME 2024
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Cross-Point Adversarial Attack Based on Feature Neighborhood Disruption Against Segment Anything Model

Yan Jiang; Guisheng Yin; Ye Yuan*; Jingjing Chen; Zhipeng Wei

  • We propose a cross-point adversarial attack method based on feature neighborhood disruption against SAM, called CP-FND attack. CP-FND aims to generate adversarial examples capable of effectively deceiving SAM under different user-specified point prompts. Specifically, CP-FND can disrupt the continuity and relevance of contextual features, thereby fooling SAM and suppressing its predicted masks.

📄 Publications (google scholar citations +)

* Corresponding author $\dagger$ Equal contribution

2025

  • Xue Zhang$\dagger$, Yanxia Wu$\dagger$, Guoyin Zhang, Ye Yuan*, Guangliang Cheng and Yulei Wu, “Shape-Dependent Dynamic Label Assignment for Oriented Remote Sensing Object Detection,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 132-146, 2025. [link] [JCR Q1, 中科院二区 Top, IF: 4.7]

2024

  • Xu Wang$\dagger$, Yanxia Wu$\dagger$, Ye Yuan*, Yan Fu and Xue Zhang, “Unpaired Image Despeckling Based on Adversarial Speckle Generation,” in Proceedings of IEEE International Conference on Multimedia and Expo (ICME), 2024, pp. 1-6. [link] [CCF-B会议]
  • Yan Jiang, Guisheng Yin, Ye Yuan*, Jingjing Chen and Zhipeng Wei, “Cross-Point Adversarial Attack Based on Feature Neighborhood Disruption Against Segment Anything Model,” in Proceedings of IEEE International Conference on Multimedia and Expo (ICME), 2024, pp. 1-6. [link] [CCF-B会议]
  • Xu Wang, Yanxia Wu, Changting Shi*, Ye Yuan and Xue Zhang, “ANED-Net: Adaptive Noise Estimation and Despeckling Network for SAR Image,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 4036-4051, 2024. [link] [JCR Q1, 中科院二区 Top, IF: 4.7]
  • Yan Jiang, Guisheng Yin, Weipeng Jing, Linda Mohaisen, Mahmoud Emam and Ye Yuan*, “Box-Spoof Attack Against Single Object Tracking,” Applied Intelligence, vol. 54, no. 2, pp. 1585-1601, 2024. [link] [JCR Q2, 中科院二区, CCF-C, IF: 3.4]

2023

  • Ye Yuan, Yanxia Wu*, Pengming Feng, Yan Fu and Yulei Wu, “Segmentation-Guided Semantic-Aware Self-Supervised Denoising for SAR Image,” IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-16, 2023, Art no. 5218416. [link] [JCR Q1, 中科院一区, CCF-B, IF: 7.5]

2022

  • Ye Yuan$\dagger$, Yanxia Wu$\dagger$, Chuheng Tang, Yan Fu*, Yulei Wu, Yan Jiang and Yize Zhao, “Self-calibrated dilated convolutional neural networks for SAR image despeckling,” International Journal of Remote Sensing, vol. 43, no. 17, pp. 6483-6508, 2022. [link] [JCR Q2, 中科院三区, IF: 3.0]
  • Ye Yuan, Jian Guan*, Pengming Feng and Yanxia Wu, “A Practical Solution for SAR Despeckling With Adversarial Learning Generated Speckled-to-Speckled Images,” IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 4004705. [link] [JCR Q1, 中科院二区, CCF-C, IF: 4.0]

2021

  • Ye Yuan, Yanxia Wu*, Yan Fu, Yulei Wu, Lidan Zhang and Yan Jiang, “An Advanced SAR Image Despeckling Method by Bernoulli-Sampling-Based Self-Supervised Deep Learning,” Remote Sensing, vol. 13, no. 18, pp. 3636, 2021. [link] [JCR Q1, 中科院二区 Top, IF: 4.2]
  • Ye Yuan, Yan Jiang, Yanxia Wu* and Richard Jiang, “Self-Calibrated Convolutional Neural Network for SAR Image Despeckling,” in Proceddings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2021, pp. 399-402. [link] [EI会议]

2020 and before

  • Yanxia Wu*, Ye Yuan, Jian Guan, Libo Yin, Jinyong Chen and Ge Zhang, “Joint Convolutional Neural Network for Small-Scale Ship Classification in SAR Images,” in Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2019, pp. 2619-2622. [link] [EI会议]
  • Ye Yuan*, Shouzheng Li, Xingjian Zhang and Jianguo Sun, “A Comparative Analysis of SVM, Naive Bayes and GBDT for Data Faults Detection in WSNs,” in Proceedings of IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C), 2018, pp. 394-399. [link] [CCF-B会议]

💠 Fundings

  • 哈尔滨工程大学-计算机科学与技术学院, 博士研究生科研创新基金, 语义感知型SAR图像自监督去噪方法研究, 2022-2023, 主持

📑 Services

Invited Reviewer for conferences:

  • 2024 IEEE International Conference on Multimedia and Expo (ICME)

Invited Reviewer for journals:

  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Geoscience and Remote Sensing Letters
  • Knowledge-Based Systems
  • Signal Processing
  • Computers and Electrical Engineering
  • Computers and Electronics in Agriculture
  • International Journal of Communication Systems