Shizhen Chang

Linköping University

📧: shizhen.chang@liu.se

📧: szchang@ieee.org

I am an Assistant Professor founded by the Wallenberg AI, Autonomous Systems, and Software Program (WASP) at Linköping University, affiliated with the Information Coding (ICG) division at the Department of Electrical Engineering (ISY). My research focuses on the intersection of machine learning and digital forensics, particularly in the application of deep learning techniques for image processing.

With a specialization in deep learning, I am adept at addressing a wide range of detection problems, including change detection, anomaly/outlier detection, and copy-move forgery detection. My expertise spans various types of data, from optical satellite images to natural images and high-dimensional instance data.

📢 New opening for PhD and Postdoc positions

S. Chang, "Can Deep Network Balance Copy-Move Forgery Detection and Distinguishment?" arXiv preprint, doi: 2305.10247, 2023.
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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.
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S. Chang and P. Ghamisi, "Changes to Captions: An Attentive Network for Remote Sensing Change Captioning," IEEE Trans. Image Process., vol. 32, pp. 6047-6060, 2023.
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S. Chang, M. Kopp, and P. Ghamisi, "Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks," arXiv preprint, doi: 2304.01101, 2023.
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S. Chang, M. Kopp, and P. Ghamisi, "Sketched Multiview Subspace Learning for Hyperspectral Anomalous Change Detection," IEEE Trans. Geosci. Remote. Sens., vol. 60, pp. 1-12, 2022.
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S. Chang and P. Ghamisi, "Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection," IEEE Trans. Geosci. Remote. Sens., vol. 60, pp. 1-13, 2022.
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S. Chang, B. Du, and L. Zhang, "A Subspace Selection-based Discriminative Forest Method for Hyperspectral Anomaly Detection," IEEE Trans. Geosci. Remote. Sens., vol. 58, no. 6, pp. 4033-4046, 2020.
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S. Chang, B. Du, and L. Zhang, "BASO: A Background-Anomaly Component Projection and Separation Optimized Filter for Anomaly Detection in Hyperspectral Images," IEEE Trans. Geosci. Remote. Sens., vol. 56, no. 7, pp. 3747-3761, 2018.
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S. Chang, B. Du, and L. Zhang, "Positive and Unlabeled Learning with Class-prior Approximation," IJCAI, 2020.
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