Outlier Exposure for Open Set Crop Recognition From Multitemporal Image Sequences-Reference-Cited by-同舟云学术

Outlier Exposure for Open Set Crop Recognition From Multitemporal Image Sequences

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Carvalho Thiago¹^ORCID,Martinez Jorge A. Chamorro¹^ORCID,Oliveira Hugo²^ORCID,Santos Jefersson A. dos³^ORCID,Feitosa Raul Queiroz¹^ORCID

Affiliation:

1. Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil

2. Institute of Mathematics and Statistics (IME), University of São Paulo (USP), São Paulo, Brazil

3. Department of Computing Science and Mathematics, University of Stirling, Stirling, Scotland, U.K.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG), and Fundação de Amparo à Pesquisa do Estado de São Paulo

Fundação de Amparo à Pesquisa do Estado de Minas Gerais

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10042432.pdf?arnumber=10042432

Reference16 articles.

1. A deep semantic segmentation-based algorithm to segment crops and weeds in agronomic color images

2. Campo Verde Database: Seeking to Improve Agricultural Remote Sensing of Tropical Areas

3. CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images

4. Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes

5. LEM BENCHMARK DATABASE FOR TROPICAL AGRICULTURAL REMOTE SENSING APPLICATION

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