Sylvain Lobry

1.2k citations
31 papers · 773 · h-index 13

Impact in

Papers in

Sylvain Lobry

30 papers receiving 762 citations

Peers

Sylvain Lobry
Comparison fields: 5 of 80
  • Computer Vision and Pattern Recognition 403
  • Media Technology 166
  • Geography, Planning and Development 64
  • Transportation 52
  • Artificial Intelligence 229
Replace H. Lexie Yang with:
H. Lexie Yang United States
Anil Cheriyadat United States
Lionel Gueguen Italy
Patrick Helber Germany
Dalton Lunga United States
Mingqiang Guo China
Liangcun Jiang China
Zhitong Xiong Germany
Conrad M Albrecht Germany
Xianwei Zheng China
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Citations per field
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Citations per year

Countries citing papers authored by Sylvain Lobry

Since Specialization
Citations

This map shows the geographic impact of Sylvain Lobry's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sylvain Lobry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sylvain Lobry more than expected).

Fields of papers citing papers by Sylvain Lobry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sylvain Lobry. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sylvain Lobry. The network helps show where Sylvain Lobry may publish in the future.

Co-authors

The 25 scholars most cited alongside Sylvain Lobry, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sylvain Lobry Line = papers co-authored together Sylvain Lobry links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020174
2 2020113
3 201997
4 201874
5 201845
6 202240
7 202133
8 202129
9 201620
10 202020
11 201919
12 202116
13 201915
14 202012
15 202211
16 20209
17
Land-use characterisation using Google Street View pictures and OpenStreetMap
20188
18 20197
19 20197
20 20185

About Sylvain Lobry

Sylvain Lobry is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Global and Planetary Change and Atmospheric Science, having authored 31 papers that have together received 773 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (10 papers), Advanced Image and Video Retrieval Techniques (10 papers), Domain Adaptation and Few-Shot Learning (9 papers), Remote-Sensing Image Classification (6 papers), Land Use and Ecosystem Services (4 papers), Remote Sensing and Land Use (3 papers), Advanced Neural Network Applications (3 papers) and COVID-19 epidemiological studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (403 citations), Media Technology (166 citations), Geography, Planning and Development (64 citations), Transportation (52 citations) and Artificial Intelligence (229 citations). Sylvain Lobry has collaborated with scholars based in France, Netherlands and Switzerland. Frequent co-authors include Devis Tuia, Diego Marcos, John E. Vargas-Muñoz, Benjamin Kellenberger, Lloyd Haydn Hughes, Michael Schmitt, Shivangi Srivastava, Alexandre X. Falcão, Begüm Demir and Bertrand Le Saux. Their work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, The Science of The Total Environment and IEEE Geoscience and Remote Sensing Magazine.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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