Selected Publications

Vision and Language Models for Remote Sensing

Y. Xu, W. Yu, P. Ghamisi, M. Kopp, and S. Hochreiter, “Txt2Img-MHN: Remote sensing image generation from text using modern hopfield networks,” IEEE Trans. Image Process., vol. 32, pp. 5737-5750, 2023.
[Paper] [Code] [Video]

Trustworthy Remote Sensing Models

Y. Xu, T. Bai, W. Yu, S. Chang, P. M. Atkinson, and P. Ghamisi, “AI security for geoscience and remote sensing: Challenges and future trends,” IEEE Geosci. Remote Sens. Mag., vol. 11, no. 2, pp. 60-85, 2023.
[Paper]

N. Dräger, Y. Xu, and P. Ghamisi, “Backdoor attacks for remote sensing data with wavelet transform,” IEEE Trans. Geosci. Remote Sens., vol. 61, pp. 1−15, 2023.
[Paper] [Code]

Y. Xu and P. Ghamisi, “Universal adversarial examples in remote sensing: Methodology and benchmark,” IEEE Trans. Geosci. Remote Sens., vol. 60, pp. 1−15, 2022. (ESI Highly Cited Paper)
[Paper] [Data] [Code] [Video]

Y. Xu, B. Du, and L. Zhang, “Self-attention context network: Addressing the threat of adversarial attacks for hyperspectral image classification,” IEEE Trans. Image Process., vol. 30, pp. 8671-8685, 2021.
[Paper] [Code]

Y. Xu, B. Du, and L. Zhang, “Assessing the threat of adversarial examples on deep neural networks for remote sensing scene classification: Attacks and defenses,” IEEE Trans. Geosci. Remote Sens., vol. 59, no. 2, pp. 1604−1617, 2021. (ESI Highly Cited Paper)
[Paper]

Intelligent Remote Sensing Data Interpretation

Y. Xu and P. Ghamisi, “Consistency-regularized region-growing network for semantic segmentation of urban scenes with point-level annotations,” IEEE Trans. Image Process., vol. 31, pp. 5038–5051, 2022.
[Paper] [Code]

Y. Xu, B. Du, and L. Zhang, “Robust self-ensembling network for hyperspectral image classification,” IEEE Trans. Neural Netw. Learn. Syst., doi: 10.1109/TNNLS.2022.3198142, 2022.
[Paper] [Code]

Y. Xu, B. Du, L. Zhang, D. Cerra, M. Pato, E. Carmona, S. Prasad, N. Yokoya, R. Hansch, and B. Le Saux, “Advanced multi-sensor optical remote sensing for urban land use and land cover classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest,” in IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 12, no. 6, pp. 1709−1724, 2019. (ESI Highly Cited Paper)
[Paper] [Data]

Y. Xu, B. Du, F. Zhang, and L. Zhang, “Hyperspectral image classification via a random patches network,” ISPRS J. Photogram. Remote Sens., vol. 142, no. 10, pp. 344–357, 2018. (ESI Highly Cited Paper)
[Paper] [Code]

Y. Xu, L. Zhang, B. Du, and F. Zhang, “Spectral-spatial unified networks for hyperspectral image classification,” IEEE Trans. Geosci. Remote Sens., vol. 56, no. 10, pp. 5893−5909, 2018. (ESI Highly Cited Paper)
[Paper] [Code]

AI for Environmental Monitoring

O. Ghorbanzadeh, Y. Xu, P. Ghamisi, M. Kopp, and D. Kreil, “Landslide4sense: Reference benchmark data and deep learning models for landslide detection,” IEEE Trans. Geosci. Remote Sens., vol. 60, pp. 1-17, 2022.
[Paper] [Data] [Code]

Cross-Domain Semantic Segmentation of Urban Scenes

Y. Xu, F. He, B. Du, D. Tao, and L. Zhang, “Self-ensembling GAN for cross-domain semantic segmentation,” IEEE Trans. Multimedia, doi: 10.1109/TMM.2022.3229976, 2022.
[Paper] [Code]

L. Song, Y. Xu, L. Zhang, B. Du, Q. Zhang, and X. Wang, “Learning from synthetic images via active pseudo-labeling,” IEEE Trans. Image Process., vol. 29, pp. 6452-6465, 2020.
[Paper] [Code]

Y. Xu, B. Du, L. Zhang, Q. Zhang, G. Wang, and L. Zhang, “Self-ensembling attention networks: Addressing domain shift for semantic segmentation,” in Proc. AAAI Conf. Artif. Intell., vol. 33, pp. 5581−5588, 2019.
[Paper] [Code]

Research Grants

Zenith Project supported by the Faculty of Science and Engineering at LiU, 2024 – 2028, PI.
– Multimodal remote sensing for climate monitoring.
Vinnova Project supported by Swedish Agency for Innovation Systems, 2023 – 2026, PI.
– Community driven approach to 3D hyperspectral AI for universal biodiversity classification.

Academic Services and Activities

Co-Lead of the WG-BEN in IEEE GRSS Image Analysis and Data Fusion Technical Committee, 2022 – Now.
Guest Editor of Special Issue on Intelligent Remote Sensing Data Interpretation, Remote Sensing, 2022 – 2023.
Guest Editor of Special Issue on Adversarial Attacks and Defenses for Remote Sensing Data, Remote Sensing, 2022 – 2023.
Guest Editor of Special Issue on Remote Sensing for Disaster Response, Frontiers in Remote Sensing, 2022 – 2023.
Guest Editor of Special Issue on Remote Sensing for Ecosystem Studies, Frontiers in Remote Sensing, 2022 – 2023.
Organizing Committee Member of Landslide4Sense 2022 Competition.
Technical Committee Member of CVPR 2022 Workshop on EARTHVISION.
Program Committee Member of IJCAI 2022 Workshop on CDCEO.
Program Committee Member of CIKM 2021 Workshop on CDCEO.
Chapter Chair of the IEEE GRSS Wuhan Student Branch, 2017 – 2020.
1st Place in 2018 IEEE GRSS Data Fusion Contest.

Journal Reviewer

IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Big Data
IEEE Journal of Selected Topics on Applied Remote Sensing
IEEE Geoscience and Remote Sensing Letters
ISPRS Journal of Photogrammetry and Remote Sensing
Pattern Recognition
Neural Networks

Teaching

Artificial Intelligence for Remote Sensing at Humboldt University of Berlin, Co-Instructor, Summer 2023.

Contact

yonghaoxu@ieee.org; yonghao.xu@liu.se

Campus Valla, Building B, 581 83 Linköping, Sweden

Selected Publications

Vision and Language Models for Remote Sensing

Y. Xu, W. Yu, P. Ghamisi, M. Kopp, and S. Hochreiter, “Txt2Img-MHN: Remote sensing image generation from text using modern hopfield networks,” IEEE Trans. Image Process., vol. 32, pp. 5737-5750, 2023. [Paper] [Code] [Video]

Trustworthy Remote Sensing Models

Y. Xu, T. Bai, W. Yu, S. Chang, P. M. Atkinson, and P. Ghamisi, “AI security for geoscience and remote sensing: Challenges and future trends,” IEEE Geosci. Remote Sens. Mag., vol. 11, no. 2, pp. 60-85, 2023. [Paper]

N. Dräger, Y. Xu, and P. Ghamisi, “Backdoor attacks for remote sensing data with wavelet transform,” IEEE Trans. Geosci. Remote Sens., vol. 61, pp. 1−15, 2023. [Paper] [Code]

Y. Xu and P. Ghamisi, “Universal adversarial examples in remote sensing: Methodology and benchmark,” IEEE Trans. Geosci. Remote Sens., vol. 60, pp. 1−15, 2022. (ESI Highly Cited Paper) [Paper] [Data] [Code] [Video]

Y. Xu, B. Du, and L. Zhang, “Self-attention context network: Addressing the threat of adversarial attacks for hyperspectral image classification,” IEEE Trans. Image Process., vol. 30, pp. 8671-8685, 2021. [Paper] [Code]

Y. Xu, B. Du, and L. Zhang, “Assessing the threat of adversarial examples on deep neural networks for remote sensing scene classification: Attacks and defenses,” IEEE Trans. Geosci. Remote Sens., vol. 59, no. 2, pp. 1604−1617, 2021. (ESI Highly Cited Paper) [Paper]

Intelligent Remote Sensing Data Interpretation

Y. Xu and P. Ghamisi, “Consistency-regularized region-growing network for semantic segmentation of urban scenes with point-level annotations,” IEEE Trans. Image Process., vol. 31, pp. 5038–5051, 2022. [Paper] [Code]

Y. Xu, B. Du, and L. Zhang, “Robust self-ensembling network for hyperspectral image classification,” IEEE Trans. Neural Netw. Learn. Syst., doi: 10.1109/TNNLS.2022.3198142, 2022. [Paper] [Code]

Y. Xu, B. Du, F. Zhang, and L. Zhang, “Hyperspectral image classification via a random patches network,” ISPRS J. Photogram. Remote Sens., vol. 142, no. 10, pp. 344–357, 2018. (ESI Highly Cited Paper) [Paper] [Code]

Y. Xu, L. Zhang, B. Du, and F. Zhang, “Spectral-spatial unified networks for hyperspectral image classification,” IEEE Trans. Geosci. Remote Sens., vol. 56, no. 10, pp. 5893−5909, 2018. (ESI Highly Cited Paper) [Paper] [Code]

AI for Environmental Monitoring

O. Ghorbanzadeh, Y. Xu, P. Ghamisi, M. Kopp, and D. Kreil, “Landslide4sense: Reference benchmark data and deep learning models for landslide detection,” IEEE Trans. Geosci. Remote Sens., vol. 60, pp. 1-17, 2022. [Paper] [Data] [Code]

Cross-Domain Semantic Segmentation of Urban Scenes

Y. Xu, F. He, B. Du, D. Tao, and L. Zhang, “Self-ensembling GAN for cross-domain semantic segmentation,” IEEE Trans. Multimedia, doi: 10.1109/TMM.2022.3229976, 2022. [Paper] [Code]

L. Song, Y. Xu, L. Zhang, B. Du, Q. Zhang, and X. Wang, “Learning from synthetic images via active pseudo-labeling,” IEEE Trans. Image Process., vol. 29, pp. 6452-6465, 2020. [Paper] [Code]

Y. Xu, B. Du, L. Zhang, Q. Zhang, G. Wang, and L. Zhang, “Self-ensembling attention networks: Addressing domain shift for semantic segmentation,” in Proc. AAAI Conf. Artif. Intell., vol. 33, pp. 5581−5588, 2019. [Paper] [Code]

Research Grants

Zenith Project supported by the Faculty of Science and Engineering at LiU, 2024 – 2028, PI. – Multimodal remote sensing for climate monitoring.

Vinnova Project supported by Swedish Agency for Innovation Systems, 2023 – 2026, PI. – Community driven approach to 3D hyperspectral AI for universal biodiversity classification.

Academic Services and Activities

Co-Lead of the WG-BEN in IEEE GRSS Image Analysis and Data Fusion Technical Committee, 2022 – Now.

Guest Editor of Special Issue on Intelligent Remote Sensing Data Interpretation, Remote Sensing, 2022 – 2023.

Guest Editor of Special Issue on Adversarial Attacks and Defenses for Remote Sensing Data, Remote Sensing, 2022 – 2023.

Guest Editor of Special Issue on Remote Sensing for Disaster Response, Frontiers in Remote Sensing, 2022 – 2023.

Guest Editor of Special Issue on Remote Sensing for Ecosystem Studies, Frontiers in Remote Sensing, 2022 – 2023.

Organizing Committee Member of Landslide4Sense 2022 Competition.

Technical Committee Member of CVPR 2022 Workshop on EARTHVISION.

Program Committee Member of IJCAI 2022 Workshop on CDCEO.

Program Committee Member of CIKM 2021 Workshop on CDCEO.

Chapter Chair of the IEEE GRSS Wuhan Student Branch, 2017 – 2020.

1st Place in 2018 IEEE GRSS Data Fusion Contest.

Journal Reviewer

IEEE Transactions on Geoscience and Remote Sensing

IEEE Transactions on Neural Networks and Learning Systems

IEEE Transactions on Information Forensics and Security

IEEE Transactions on Circuits and Systems for Video Technology

IEEE Transactions on Big Data

IEEE Journal of Selected Topics on Applied Remote Sensing

IEEE Geoscience and Remote Sensing Letters

ISPRS Journal of Photogrammetry and Remote Sensing

Pattern Recognition

Neural Networks

Teaching

Artificial Intelligence for Remote Sensing at Humboldt University of Berlin, Co-Instructor, Summer 2023.

Contact

yonghaoxu@ieee.org; yonghao.xu@liu.se

Campus Valla, Building B, 581 83 Linköping, Sweden

© 2023 Yonghao Xu. Powered by Startbootstrap and hosted by Github Pages. Last updated on December 2023.

Y. Xu, W. Yu, P. Ghamisi, M. Kopp, and S. Hochreiter, “Txt2Img-MHN: Remote sensing image generation from text using modern hopfield networks,” IEEE Trans. Image Process., vol. 32, pp. 5737-5750, 2023.
[Paper] [Code] [Video]

Y. Xu, T. Bai, W. Yu, S. Chang, P. M. Atkinson, and P. Ghamisi, “AI security for geoscience and remote sensing: Challenges and future trends,” IEEE Geosci. Remote Sens. Mag., vol. 11, no. 2, pp. 60-85, 2023.
[Paper]

N. Dräger, Y. Xu, and P. Ghamisi, “Backdoor attacks for remote sensing data with wavelet transform,” IEEE Trans. Geosci. Remote Sens., vol. 61, pp. 1−15, 2023.
[Paper] [Code]

Y. Xu and P. Ghamisi, “Universal adversarial examples in remote sensing: Methodology and benchmark,” IEEE Trans. Geosci. Remote Sens., vol. 60, pp. 1−15, 2022. (ESI Highly Cited Paper)
[Paper] [Data] [Code] [Video]

Y. Xu, B. Du, and L. Zhang, “Self-attention context network: Addressing the threat of adversarial attacks for hyperspectral image classification,” IEEE Trans. Image Process., vol. 30, pp. 8671-8685, 2021.
[Paper] [Code]

Y. Xu, B. Du, and L. Zhang, “Assessing the threat of adversarial examples on deep neural networks for remote sensing scene classification: Attacks and defenses,” IEEE Trans. Geosci. Remote Sens., vol. 59, no. 2, pp. 1604−1617, 2021. (ESI Highly Cited Paper)
[Paper]

Y. Xu and P. Ghamisi, “Consistency-regularized region-growing network for semantic segmentation of urban scenes with point-level annotations,” IEEE Trans. Image Process., vol. 31, pp. 5038–5051, 2022.
[Paper] [Code]

Y. Xu, B. Du, and L. Zhang, “Robust self-ensembling network for hyperspectral image classification,” IEEE Trans. Neural Netw. Learn. Syst., doi: 10.1109/TNNLS.2022.3198142, 2022.
[Paper] [Code]

Y. Xu, B. Du, F. Zhang, and L. Zhang, “Hyperspectral image classification via a random patches network,” ISPRS J. Photogram. Remote Sens., vol. 142, no. 10, pp. 344–357, 2018. (ESI Highly Cited Paper)
[Paper] [Code]

Y. Xu, L. Zhang, B. Du, and F. Zhang, “Spectral-spatial unified networks for hyperspectral image classification,” IEEE Trans. Geosci. Remote Sens., vol. 56, no. 10, pp. 5893−5909, 2018. (ESI Highly Cited Paper)
[Paper] [Code]

O. Ghorbanzadeh, Y. Xu, P. Ghamisi, M. Kopp, and D. Kreil, “Landslide4sense: Reference benchmark data and deep learning models for landslide detection,” IEEE Trans. Geosci. Remote Sens., vol. 60, pp. 1-17, 2022.
[Paper] [Data] [Code]

Y. Xu, F. He, B. Du, D. Tao, and L. Zhang, “Self-ensembling GAN for cross-domain semantic segmentation,” IEEE Trans. Multimedia, doi: 10.1109/TMM.2022.3229976, 2022.
[Paper] [Code]

L. Song, Y. Xu, L. Zhang, B. Du, Q. Zhang, and X. Wang, “Learning from synthetic images via active pseudo-labeling,” IEEE Trans. Image Process., vol. 29, pp. 6452-6465, 2020.
[Paper] [Code]

Y. Xu, B. Du, L. Zhang, Q. Zhang, G. Wang, and L. Zhang, “Self-ensembling attention networks: Addressing domain shift for semantic segmentation,” in Proc. AAAI Conf. Artif. Intell., vol. 33, pp. 5581−5588, 2019.
[Paper] [Code]

Zenith Project supported by the Faculty of Science and Engineering at LiU, 2024 – 2028, PI.
– Multimodal remote sensing for climate monitoring.

Vinnova Project supported by Swedish Agency for Innovation Systems, 2023 – 2026, PI.
– Community driven approach to 3D hyperspectral AI for universal biodiversity classification.

© 2023 Yonghao Xu. Powered by Startbootstrap and hosted by Github Pages.
Last updated on December 2023.