User-Guided Data Expansion Modeling to Train Deep Neural Networks With Little Supervision-Reference-Cited by-同舟云学术

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User-Guided Data Expansion Modeling to Train Deep Neural Networks With Little Supervision

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

de Souza Italos Estilon¹^ORCID,Lessio Cazarin Caroline²^ORCID,Veronez Mauricio Roberto³^ORCID,Gonzaga Luiz³^ORCID,Xavier Falcao Alexandre¹^ORCID

Affiliation:

1. Institute of Computing, State University of Campinas, Campinas, Brazil

2. CENPES-PETROBRAS, Rio de Janeiro, Brazil

3. Vizlab|X-Reality and Geoinformatics Laboratory, Graduate Programme in Applied Computing, Unisinos University, São Leopoldo, Brazil

Funder

São Paulo Research Foundation

National Council for Scientific and Technological Development

Petróleo Brasileiro S. A.

Agência Nacional do Petróleo, Gás Natural e Biocombustíveis

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09866029.pdf?arnumber=9866029

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automatic Multipath Annotation for Conventional Automotive Radar Datasets;IEEE Sensors Journal;2024-04-15

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