In order to ensure homogeneity in performance assessment of proposed algorithms for information extraction in the Earth Observation (EO) domain, standardized remotely sensed datasets are particularly useful and welcome. Fully aware of this principle, the IEEE Geoscience and Remote Sensing Society (GRSS) and especially its Image Analysis and Data Fusion Technical Committee (IADF), has been organizing for some years now the Data Fusion Contest (DFC). In the DFC, one specific dataset is made available to the scientific community, which can download it and use it to test its newly developed algorithms. The consistence of the starting dataset across participating groups ensures the significance of assessing and ranking results, to finally procla...
Earth observation is the field of science concerned with the problem of monitoring and modeling the ...
This report aims to support the work of the JRC.B6 (Digital Economy Unit), which provides scientific...
International audiencePresents information on the 2017 IEEE Geoscience and Remote Sensing Society Da...
In order to ensure homogeneity in performance assessment of proposed algorithms for information extr...
The issue of homogeneity in performance assessment of proposed algorithms for information extraction...
The 2020 Data Fusion Contest, organized by the IEEE Geoscience and Remote Sensing Society (GRSS) Ima...
In the era of deep learning, annotated datasets have become a crucial asset to the remote sensing co...
Since 2006, the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience ...
International audienceIn this article, we elaborate on the scientific outcomes of the 2021 Data Fusi...
In this paper, we present the scientific outcomes of the 2017 Data Fusion Contest organized by the I...
International audienceThe 2018 Data Fusion Contest, organized by the Image Analysis and Da...
The Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (...
Both development and application of remote sensing involves a considerable expenditure of material a...
Data availability plays a central role in any machine learning setup, especially since the rise of d...
International audienceThe 2017 Data Fusion Contest, organized by the Image Analysis and Data Fusion ...
Earth observation is the field of science concerned with the problem of monitoring and modeling the ...
This report aims to support the work of the JRC.B6 (Digital Economy Unit), which provides scientific...
International audiencePresents information on the 2017 IEEE Geoscience and Remote Sensing Society Da...
In order to ensure homogeneity in performance assessment of proposed algorithms for information extr...
The issue of homogeneity in performance assessment of proposed algorithms for information extraction...
The 2020 Data Fusion Contest, organized by the IEEE Geoscience and Remote Sensing Society (GRSS) Ima...
In the era of deep learning, annotated datasets have become a crucial asset to the remote sensing co...
Since 2006, the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience ...
International audienceIn this article, we elaborate on the scientific outcomes of the 2021 Data Fusi...
In this paper, we present the scientific outcomes of the 2017 Data Fusion Contest organized by the I...
International audienceThe 2018 Data Fusion Contest, organized by the Image Analysis and Da...
The Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (...
Both development and application of remote sensing involves a considerable expenditure of material a...
Data availability plays a central role in any machine learning setup, especially since the rise of d...
International audienceThe 2017 Data Fusion Contest, organized by the Image Analysis and Data Fusion ...
Earth observation is the field of science concerned with the problem of monitoring and modeling the ...
This report aims to support the work of the JRC.B6 (Digital Economy Unit), which provides scientific...
International audiencePresents information on the 2017 IEEE Geoscience and Remote Sensing Society Da...