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Seismic Interpretation

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TitleStatusHype
A Machine Learning Benchmark for Facies ClassificationCode1
Man-recon: manifold learning for reconstruction with deep autoencoder for smart seismic interpretationCode1
A novel attention model for salient structure detection in seismic volumes—0
Automatic classification of geologic units in seismic images using partially interpreted examples—0
Binary Segmentation of Seismic Facies Using Encoder-Decoder Neural Networks—0
Characterization of migrated seismic volumes using texture attributes: a comparative study—0
Effective Data Selection for Seismic Interpretation through Disagreement—0
Example Forgetting: A Novel Approach to Explain and Interpret Deep Neural Networks in Seismic Interpretation—0
Fault Detection Using Color Blending and Color Transformations—0
Ground Roll Suppression using Convolutional Neural Networks—0
Volumetric Supervised Contrastive Learning for Seismic Semantic Segmentation—0
A Large-scale Benchmark on Geological Fault Delineation Models: Domain Shift, Training Dynamics, Generalizability, Evaluation and Inferential Behavior—0
A comparative study of texture attributes for characterizing subsurface structures in seismic volumes—0
Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation—0
Parallel Computation of PDFs on Big Spatial Data Using Spark—0
SalSi: A new seismic attribute for salt dome detection—0
Structure Label Prediction Using Similarity-Based Retrieval and Weakly-Supervised Label Mapping—0
Subsurface structure analysis using computational interpretation and learning: A visual signal processing perspective—0
The role of visual saliency in the automation of seismic interpretation—0
Learning to Decouple and Generate Seismic Random Noise via Invertible Neural NetworkCode0
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