Simon Madec
Impact in
- Plant Science top 2%
- Smart Agriculture and AI
- Genetics and Plant Breeding
- Wheat and Barley Genetics and Pathology
- Ecology top 5%
- Remote Sensing in Agriculture
Papers in
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- Smart Agriculture and AI 13
- Ecology 8
- Remote Sensing in Agriculture 8
- Co-authors
- Frédéric Baret (15 shared papers)Benoît de Solan (7 shared papers)Alexis Comar (7 shared papers)Hao Lü (2 shared papers)Dan Dutartre (3 shared papers)Shouyang Liu (3 shared papers)Matthieu Hemmerlé (2 shared papers)Xiuliang Jin (2 shared papers)
In The Last Decade
Simon Madec
19 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 39
- Plant Science 993
- Ecology 370
- Geology 52
- Environmental Engineering 89
- Computer Vision and Pattern Recognition 94
Countries citing papers authored by Simon Madec
This map shows the geographic impact of Simon Madec'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 Simon Madec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Madec more than expected).
Fields of papers citing papers by Simon Madec
This network shows the impact of papers produced by Simon Madec. 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 Simon Madec. The network helps show where Simon Madec may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Madec, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 287 | |
| 2 | 2018 | 253 | |
| 3 | 2020 | 208 | |
| 4 | 2019 | 125 | |
| 5 | 2021 | 116 | |
| 6 | 2018 | 64 | |
| 7 | 2021 | 62 | |
| 8 | 2021 | 48 | |
| 9 | 2022 | 43 | |
| 10 | 2019 | 41 | |
| 11 | 2020 | 37 | |
| 12 | 2018 | 9 | |
| 13 | 2021 | 6 | |
| 14 | 2023 | 6 | |
| 15 | 2021 | 3 | |
| 16 | 2023 | 3 | |
| 17 | The problem of radiometric calibration for UAV observations acquired under changing illumination conditions | 2017 | 1 |
| 18 | The P2S2 segmentation dataset: annotated in-field multi-crop RGB images acquired under various conditions | 2019 | 1 |
| 19 | 2019 | 1 |
About Simon Madec
Simon Madec is a scholar working on Plant Science, Ecology, Media Technology, Environmental Engineering and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 1.3k indexed citations. Recurring topics across this work include Smart Agriculture and AI (13 papers), Remote Sensing in Agriculture (8 papers), Advanced Neural Network Applications (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Remote Sensing and LiDAR Applications (1 paper), Remote-Sensing Image Classification (1 paper) and Calibration and Measurement Techniques (1 paper). The work is most often cited by research in Plant Science (993 citations), Ecology (370 citations), Geology (52 citations), Environmental Engineering (89 citations) and Computer Vision and Pattern Recognition (94 citations). Simon Madec has collaborated with scholars based in France, Japan and China. Frequent co-authors include Frédéric Baret, Benoît de Solan, Alexis Comar, Hao Lü, Dan Dutartre, Shouyang Liu, Matthieu Hemmerlé, Xiuliang Jin, Florent Duyme and Wei Guo. Their work appears in journals such as Plant Phenomics, Plant Methods, Frontiers in Plant Science, Remote Sensing of Environment and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
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.