论文信息 - Seismic fault detection based on 3D Unet++ model - 字舞流文

Seismic fault detection based on 3D Unet++ model

Guangmin Hu | Xingmiao Yao | Yufei Cai | Dun Yang | Wen Zou

[1] Kristofer M. Tingdahl,et al. Semi‐automatic detection of faults in 3D seismic data , 2005 .

[2] Nima Tajbakhsh,et al. UNet++: A Nested U-Net Architecture for Medical Image Segmentation , 2018, DLMIA/ML-CDS@MICCAI.

[3] Haibo He,et al. Learning from Imbalanced Data , 2009, IEEE Transactions on Knowledge and Data Engineering.

[4] Jiaying Liu,et al. Adaptive Batch Normalization for practical domain adaptation , 2018, Pattern Recognit..

[5] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6] Xishuang Dong,et al. A scalable deep learning platform for identifying geologic features from seismic attributes , 2017 .

[7] Sergey Fomel,et al. FaultSeg3D: Using synthetic data sets to train an end-to-end convolutional neural network for 3D seismic fault segmentation , 2019, GEOPHYSICS.

[8] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.

[9] Kurt J. Marfurt,et al. Eigenstructure-based coherence computations as an aid to 3-D structural and stratigraphic mapping , 1999 .