Incremental semi-supervised learning for intelligent seismic facies identification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geophysics
Link
https://link.springer.com/content/pdf/10.1007/s11770-022-0924-8.pdf
Reference43 articles.
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3. AlRegib, G., Deriche, M., Long, Z., Di, H., Wang, Z., Alaudah, Y., Shafiq, M. A., and Alfarraj, M., 2018, Subsurface structure analysis using computational interpretation and learning: A visual signal processing perspective: IEEE Signal Processing Magazine, 35(2), 82–98.
4. Asghar, S., and Byun, J., 2021, Semi-supervised facies classification with reconstruction cooperation: First International Meeting for Applied Geoscience and Energy, SEG, Expanded Abstracts, 2173–2177.
5. Badrinarayanan, V., Kendall, A., and Cipolla, R., 2017, SegNet: A deep convolutional encoderdecoder architecture for image segmentation: IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(12), 2481–2495.
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