Self-Supervised Learning for Seismic Image Segmentation From Few-Labeled Samples
Author:
Affiliation:
1. Department of Computer Science, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
2. Institute of Mathematics and Statistics (IME), University of São Paulo (USP), São Paulo, Brazil
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), Fundação de Amparo à Pesquisa do Estado de São Paulo
Serrapilheira Institute
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology
Link
http://xplorestaging.ieee.org/ielx7/8859/9651998/09837909.pdf?arnumber=9837909
Reference27 articles.
1. Fault and horizon automatic interpretation by CNN: a case study of coalfield
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5. Unsupervised Representation Learning by Sorting Sequences
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