Optimizing Seismic Facies Classification Through Differentiable Network Architecture Search-Reference-Cited by-同舟云学术

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Optimizing Seismic Facies Classification Through Differentiable Network Architecture Search

Published:2024 Issue: Volume:62 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:

Gao Zhaoqi¹^ORCID,Wang Kezheng¹,Wang Zhiguo²^ORCID,Gao Jinghuai¹^ORCID

Affiliation:

1. School of Information and Communications Engineering and the National Engineering Laboratory for Offshore Oil Exploration, Xi’an Jiaotong University, Shaanxi, Xi’an, China

2. School of Mathematics and Statistics, Xi’an Jiaotong University, Shaanxi, Xi’an, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of the Ministry of Science and Technology of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10413525.pdf?arnumber=10413525

Reference42 articles.

1. Bayesian Convolutional Neural Networks for Seismic Facies Classification

2. An Open-Source Package for Deep-Learning-Based Seismic Facies Classification: Benchmarking Experiments on the SEG 2020 Open Data

3. Seismic Facies Segmentation via a Segformer-Based Specific Encoder–Decoder–Hypercolumns Scheme

4. Automatic Seismic Lithology Interpretation via Multiattribute Integrated Deep Learning

5. Explainable Deep Learning for Supervised Seismic Facies Classification Using Intrinsic Method

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