Journal Paper

• Kazuki Naganuma, Shunsuke Ono. Towards robust hyperspectral unmixing: Mixed noise modeling and image-domain regularization, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 8117-8138, Mar. 2024.
• Ryosuke Isono, Kazuki Naganuma, Shunsuke Ono. Robust spatiotemporal fusion of satellite images: A constrained convex optimization approach, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-16, 2024.

International Conference (Reviewed)

• Koyo Sato, Kazuki Naganuma, Shunsuke Ono. Enhancing hyperspectral anomaly detection by difference-of-convex sparse anomaly modeling, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 9921-9925, Apr. 2024.
• Kazuki Naganuma, Shunsuke Ono. Constrained hyperspectral unmixing robust to mixed noise, ASPIRE 2024, pp. 8, Mar. 2024.

Degree

• Convex Optimization Techniques for Remote Sensing Data Analysis,  Thesis,  Doctor (Engineering),  Tokyo Institute of Technology,  2024/03/26,   
• Convex Optimization Techniques for Remote Sensing Data Analysis,  Summary,  Doctor (Engineering),  Tokyo Institute of Technology,  2024/03/26,   
• Convex Optimization Techniques for Remote Sensing Data Analysis,  Exam Summary,  Doctor (Engineering),  Tokyo Institute of Technology,  2024/03/26,   

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