Deep Learning
2022
M. Gauch, M. Beck, T. Adler, D. Kotsur, S. Fiel, H. Eghbal-zadeh, J. Brandstetter, J. Kofler, M. Holzleitner, W. Zellinger, D. Klotz, S. Hochreiter, and S. Lehner (2022) Few-Shot Learning by Dimensionality Reduction in Gradient Space. arXiv:2206.03483, 2022-06-07. (more) (download)
B. Schäfl, L. Gruber, A. Bitto-Nemling, and S. Hochreiter (2022) Hopular: Modern Hopfield Networks for Tabular Data. arXiv:2206.00664, 2022-06-01. (more) (download)
H. Li, J. Zech, D. Hong, P. Ghamisi, M. Schultz, and A. Zipf (2022) Leveraging OpenStreetMap and Multimodal Remote Sensing Data with Joint Deep Learning for Wastewater Treatment Plants Detection. International Journal of Applied Earth Observation and Geoinformation, 110, 102804, 2022-06-01. (more) (download)
J. Yuan, S. Wang, C. Wu, and Y. Xu (2022) Fine-Grained Classification of Urban Functional Zones and Landscape Pattern Analysis Using Hyperspectral Satellite Imagery: A Case Study of Wuhan. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 3972 - 3991, 2022-05-12. (more) (download)
S. Venkataramanan, B. Psomas, E. Kijak, L. Amsaleg, K. Karantzalos, and Y. Avrithis (2022) It Takes Two to Tango: Mixup for Deep Metric Learning. ICLR 2022 Conference Proceedings, 2022-04-25. (more) (download)
J. Yue, L. Fang, P. Ghamisi, W. Xie, J. Li, J. Chanussot, and A. J. Plaza (2022) Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives. arXiv:2204.09120, 2022-04-18. (more) (download)
D. Klotz, F. Kratzert, M. Gauch, A. K. Sampson, J. Brandstetter, G. Klambauer, S. Hochreiter, and G. Nearing (2022) Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. Hydrology and Earth System Sciences, 26, 6, 1673-1693, 2022-03-31. (more) (download)
S. Hochreiter (2022) Toward a broad AI. Communications of the ACM, 65, 4, 56-57, 2022-03-19. (more) (download)
O. Ghorbanzadeh, K. Gholamnia, and P. Ghamisi (2022) The Application of ResU-Net and OBIA for Landslide Detection from Multi-Temporal Sentinel-2 Images. Big Earth Data, 2022-02-14. (more) (download)
Z. Li, F. Lu, H. Zhang, L. Tu, J. Li, X. Huang, C. Robinson, K. Malkin, N. Jojic, P. Ghamisi, R. Hansch, and N. Yokoya (2022) The Outcome of the 2021 IEEE GRSS Data Fusion Contest-Track MSD: Multitemporal Semantic Change Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 2022-01-24. (more) (download)
O. Ghorbanzadeh, H. Shahabi, A. Crivellari, S. Homayouni, T. Blaschke, and P. Ghamisi (2022) Landslide Detection Using Deep Learning and Object-Based Image Analysis. Landslides, 19, 4, 929, 2022-01-20. (more) (download)
W. Song, Z. Gao, R. Dian, P. Ghamisi, Y. Zhang, and J. A. Benediktsson (2022) Asymmetric Hash Code Learning for Remote Sensing Image Retrieval. IEEE Transactions on Geoscience and Remote Sensing, 60, 5617514, 1, 2022-01-14. (more) (download)
C. Persello, J. D. Wegner, R. Hänsch, D. Tuia, P. Ghamisi, M. Koeva, and G. Camps-Valls (2022) Deep Learning and Earth Observation to Support the Sustainable Development Goals. IEEE Geoscience and Remote Sensing Magazine, 10, 2, 172-200, 2022-01-14. (more) (download)
M. Lu, L. Fang, M. Li, B. Zhang, Y. Zhang, and P. Ghamisi (2022) NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery. IEEE Transactions on Geoscience and Remote Sensing, 60, 2022-01-04. (more) (download)
2021
K. Rafiezadehshahi, P. Ghamisi, B. Rasti, P. Scheunders, and R. Gloaguen (2021) Unsupervised Data Fusion with Deeper Perspective: A Novel Multi-Sensor Deep Clustering Algorithm. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021-12-06. (more) (download)
T. Adler, M. Erhard, M. Krenn, J. Brandstetter, J. Kofler, and S. Hochreiter (2021) Quantum Optical Experiments Modeled by Long Short-Term Memory. Photonics, 8, 12, 535, 2021-11-26. (more) (download)
Y. Ma, Y. Li, K. Feng, Y. Xia, Q. Huang, H. Zhang, C. Prieur, G. Licciardi, H. Malha, J. Chanussot, P. Ghamisi, R. Hansch, and N. Yokoya (2021) The Outcome of the 2021 IEEE GRSS Data Fusion Contest – Track DSE: Detection of Settlements Without Electricity. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 12375, 2021-11-24. (more) (download)
H. Shahabi, M. Rahimzad, S. T. Piralilou, O. Ghorbanzadeh, S. Homayouni, T. Blaschke, S. Lim, and a. P. Ghamisi (2021) Unsupervised Deep Learning for Landslide Detection from Multispectral Sentinel-2 Imagery. Remote Sensing, 13, 22, 4698, 2021-11-20. (more) (download)
Y. Cai, Z. Zhang, Y. Liu, P. Ghamisi, K. Li, X. Liu, and Z. Cai (2021) Large-Scale Hyperspectral Image Clustering Using Contrastive Learning. arXiv:2111.07945, 2021-11-15. (more) (download)
M. Mc Cutchan & I. Giannopoulos (2021) Towards Geographic Aware Neural Networks for Geospatial Vector Data: A Case Study on Land Use and Land Cover Classification. CEUR Workshop Proceedings, CIKM 2021, 3052, 2021-11-01. (more) (download)
A. Gruca, P. Herruzo, P. Rípodas, A. Kucik, C. Briese, M. K. Kopp, S. Hochreiter, P. Ghamisi, and D. P. Kreil (2021) CDCEO’21 – First Workshop on Complex Data Challenges in Earth Observation. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 4878–4879, 2021-10-26. (more) (download)
M. Schmitt, C. Persello, G. Vivone, D. Lunga, W. Liao, N. Yokoya, P. Ghamisi, and R. Hänsch (2021) The New Working Groups of the GRSS Technical Committee on Image Analysis and Data Fusion. IEEE Geoscience and Remote Sensing Magazine, 9, 3, 165-166, 2021-09-29. (more) (download)
Q. Li, Y. Chen, and P. Ghamisi (2021) Complementary Learning-Based Scene Classification of Remote Sensing Images With Noisy Labels. IEEE Geoscience and Remote Sensing Letters, 2021-09-29. (more) (download)
P. Ghamisi, K. R. Shahi, P. Duan, B. Rasti, S. Lorenz, R. Booysen, S. Thiele, I. C. C. Acosta, M. Kirsch, and R. Gloaguen (2021) The Potential of Machine Learning for a More Responsible Sourcing of Critical Raw Materials. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021-09-01. (more) (download)