Towards Arbitrary Noise Augmentation-Deep Learning for Sampling from Arbitrary Probability Distributions

Horger F, Würfl T, Christlein V, Maier A (2018)

Publication Type: Conference contribution

Publication year: 2018

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: SPRINGER INTERNATIONAL PUBLISHING AG

City/Town: CHAM

Pages Range: 129-137

Conference Proceedings Title: MACHINE LEARNING FOR MEDICAL IMAGE RECONSTRUCTION, MLMIR 2018

Event location: Granada ES

DOI: 10.1007/978-3-030-00129-2_15

Authors with CRIS profile

Tobias Würfl Lehrstuhl für Informatik 5 (Mustererkennung) Vincent Christlein Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung)

How to cite

APA:

Horger, F., Würfl, T., Christlein, V., & Maier, A. (2018). Towards Arbitrary Noise Augmentation-Deep Learning for Sampling from Arbitrary Probability Distributions. In MACHINE LEARNING FOR MEDICAL IMAGE RECONSTRUCTION, MLMIR 2018 (pp. 129-137). Granada, ES: CHAM: SPRINGER INTERNATIONAL PUBLISHING AG.

MLA:

Horger, Felix, et al. "Towards Arbitrary Noise Augmentation-Deep Learning for Sampling from Arbitrary Probability Distributions." Proceedings of the 1st Workshop on Machine Learning for Medical Image Reconstruction (MLMIR) held as part of the 21st Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada CHAM: SPRINGER INTERNATIONAL PUBLISHING AG, 2018. 129-137.

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