GMM-based Synthetic Samples for Classification of Hyperspectral Images with Limited Training Data

Davari A, Aptoula E, Yanikoglu B, Maier A, Riess C (2018)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2018

Journal

IEEE Geoscience and Remote Sensing Letters Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 15

Pages Range: 942-946

Journal Issue: 6

URI: https://arxiv.org/pdf/1712.04778.pdf

DOI: 10.1109/LGRS.2018.2817361

Authors with CRIS profile

Amirabbas Davari Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Christian Rieß Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen)

How to cite

APA:

Davari, A., Aptoula, E., Yanikoglu, B., Maier, A., & Riess, C. (2018). GMM-based Synthetic Samples for Classification of Hyperspectral Images with Limited Training Data. IEEE Geoscience and Remote Sensing Letters, 15(6), 942-946. https://dx.doi.org/10.1109/LGRS.2018.2817361

MLA:

Davari, Amirabbas, et al. "GMM-based Synthetic Samples for Classification of Hyperspectral Images with Limited Training Data." IEEE Geoscience and Remote Sensing Letters 15.6 (2018): 942-946.

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