Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning

Ronny Hansch; Claudio Persello; Gemine Vivone; Javiera Castillo Navarro; Alexandre Boulch; Sebastien Lefevre; Bertrand Le Saux

doi:10.1109/MGRS.2022.3219935

Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning

Ronny Hansch, Claudio Persello, Gemine Vivone, Javiera Castillo Navarro, Alexandre Boulch, Sebastien Lefevre, Bertrand Le Saux

Research output: Contribution to journal › Article › Professional

1 Citation (Scopus)

Abstract

The Image Analysis and Data Fusion (IADF) Technical Committee (TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) has been organizing the annual Data Fusion Contest (DFC) since 2006. The contest promotes the development of methods for extracting geospatial information from large-scale, multisensor, multimodal, and multitemporal data. It aims to propose new problem settings that are challenging to address with existing techniques and to establish new benchmarks for scientific challenges in remote sensing image analysis [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19].

Original language	English
Pages (from-to)	2-5
Number of pages	4
Journal	IEEE geoscience and remote sensing magazine
DOIs	https://doi.org/10.1109/MGRS.2022.3219935
Publication status	E-pub ahead of print/First online - 21 Nov 2022

Keywords

Benchmark testing
Data integration
Earth
Image analysis
Optical sensors
Remote sensing
Semantics
2023 OA procedure
ITC-ISI-JOURNAL-ARTICLE

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10.1109/MGRS.2022.3219935

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title = "Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning",

abstract = "The Image Analysis and Data Fusion (IADF) Technical Committee (TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) has been organizing the annual Data Fusion Contest (DFC) since 2006. The contest promotes the development of methods for extracting geospatial information from large-scale, multisensor, multimodal, and multitemporal data. It aims to propose new problem settings that are challenging to address with existing techniques and to establish new benchmarks for scientific challenges in remote sensing image analysis [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19].",

keywords = "Benchmark testing, Data integration, Earth, Image analysis, Optical sensors, Remote sensing, Semantics, 2023 OA procedure, ITC-ISI-JOURNAL-ARTICLE",

author = "Ronny Hansch and Claudio Persello and Gemine Vivone and {Castillo Navarro}, Javiera and Alexandre Boulch and Sebastien Lefevre and {Le Saux}, Bertrand",

note = "Publisher Copyright: IEEE",

year = "2022",

month = nov,

day = "21",

doi = "10.1109/MGRS.2022.3219935",

language = "English",

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journal = "IEEE geoscience and remote sensing magazine",

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AU - Persello, Claudio

AU - Vivone, Gemine

AU - Castillo Navarro, Javiera

AU - Boulch, Alexandre

AU - Lefevre, Sebastien

AU - Le Saux, Bertrand

N1 - Publisher Copyright: IEEE

PY - 2022/11/21

Y1 - 2022/11/21

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KW - Data integration

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KW - Image analysis

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Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning

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