Mads Dyrmann
Impact in
- Analytical Chemistry top 1%
- Spectroscopy and Chemometric Analyses
- Plant Science top 2%
- Smart Agriculture and AI
- Date Palm Research Studies
- Plant Disease Management Techniques
- Leaf Properties and Growth Measurement
Papers in
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- Species Distribution and Climate Change 10
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- Smart Agriculture and AI 22
- Leaf Properties and Growth Measurement 3
- Date Palm Research Studies 3
- Co-authors
- Henrik Skov Midtiby (5 shared papers)Rasmus Nyholm Jørgensen (24 shared papers)Anders Krogh Mortensen (8 shared papers)René Gislum (6 shared papers)Solvejg K. Mathiassen (2 shared papers)Henrik Karstoft (2 shared papers)Morten Stigaard Laursen (8 shared papers)Toke T. Høye (5 shared papers)
In The Last Decade
Mads Dyrmann
35 papers receiving 1.3k citations
Mads Dyrmann's Hit Papers
Peers
Comparison fields: 5 of 94
- Analytical Chemistry 286
- Plant Science 1.1k
- Ecological Modeling 88
- Ecology 465
- Environmental Engineering 126
Countries citing papers authored by Mads Dyrmann
This map shows the geographic impact of Mads Dyrmann'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 Mads Dyrmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mads Dyrmann more than expected).
Fields of papers citing papers by Mads Dyrmann
This network shows the impact of papers produced by Mads Dyrmann. 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 Mads Dyrmann. The network helps show where Mads Dyrmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Mads Dyrmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Plant species classification using deep convolutional neural network Hit paper breakdown → | 2016 | 527 |
| 2 | 2017 | 128 | |
| 3 | 2018 | 100 | |
| 4 | Semantic Segmentation of Mixed Crops using Deep Convolutional Neural Network | 2016 | 80 |
| 5 | 2019 | 77 | |
| 6 | 2023 | 75 | |
| 7 | 2020 | 59 | |
| 8 | 2019 | 52 | |
| 9 | 2019 | 42 | |
| 10 | Pixel-wise classification of weeds and crops in images by using a Fully Convolutional neural network | 2016 | 38 |
| 11 | 2017 | 37 | |
| 12 | 2023 | 27 | |
| 13 | 2017 | 20 | |
| 14 | 2022 | 18 | |
| 15 | 2020 | 17 | |
| 16 | 2021 | 17 | |
| 17 | 2017 | 14 | |
| 18 | 2021 | 11 | |
| 19 | Automated Classification of Seedlings Using Computer Vision | 2014 | 9 |
| 20 | 2025 | 9 |
About Mads Dyrmann
Mads Dyrmann is a scholar working on Ecological Modeling, Plant Science, Ecology, Analytical Chemistry and Insect Science, having authored 37 papers that have together received 1.4k indexed citations. Recurring topics across this work include Smart Agriculture and AI (22 papers), Remote Sensing in Agriculture (13 papers), Species Distribution and Climate Change (10 papers), Spectroscopy and Chemometric Analyses (5 papers), Remote Sensing and LiDAR Applications (4 papers), Leaf Properties and Growth Measurement (3 papers), Wildlife-Road Interactions and Conservation (3 papers) and Date Palm Research Studies (3 papers). The work is most often cited by research in Analytical Chemistry (286 citations), Plant Science (1.1k citations), Ecological Modeling (88 citations), Ecology (465 citations) and Environmental Engineering (126 citations). Mads Dyrmann has collaborated with scholars based in Denmark, France and Iran. Frequent co-authors include Henrik Skov Midtiby, Rasmus Nyholm Jørgensen, Anders Krogh Mortensen, René Gislum, Solvejg K. Mathiassen, Henrik Karstoft, Morten Stigaard Laursen, Toke T. Høye, Kim Bjerge and Søren Skovsen. Their work appears in journals such as Sensors, Ecological Informatics, Biosystems Engineering, F1000Research 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.