Example Forgetting: A Novel Approach to Explain and Interpret Deep Neural Networks in Seismic Interpretation-Reference-Cited by-同舟云学术

Example Forgetting: A Novel Approach to Explain and Interpret Deep Neural Networks in Seismic Interpretation

Published:2022 Issue: Volume:60 Page:1-12
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Benkert Ryan¹^ORCID,Aribido Oluwaseun Joseph¹,AlRegib Ghassan¹^ORCID

Affiliation:

1. School of Electrical and Computer Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, GA, USA

Funder

Center for Energy and Geo Processing, Georgia Institute of Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09782433.pdf?arnumber=9782433

Reference65 articles.

1. Joint learning for spatial context-based seismic inversion of multiple datasets for improved generalizability and robustness;mustafa;arXiv 2104 02750,2021

2. Effect of rock physics modeling in impedance inversion from seismic data using convolutional neural network

3. 3D seismic facies classification using convolutional neural network and semi-supervised generative adversarial network

4. Multi-attribute k-means clustering for salt-boundary delineation from three-dimensional seismic data

5. Deep convolutional neural networks for seismic salt-body delineation;di;Proc AAPG Annu Conv Exhib,2018

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