Raphaël Canals
- Plant Science top 2%
- Smart Agriculture and AI 12
- Analytical Chemistry top 2%
- Spectroscopy and Chemometric Analyses 4
- Ecology top 5%
- Remote Sensing in Agriculture 9
- Environmental Engineering top 5%
- Remote Sensing and LiDAR Applications 5
- Media Technology top 5%
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- Diabetic Foot Ulcer Assessment and Management 5
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- Infrared Thermography in Medicine 5
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- Spectroscopy Techniques in Biomedical and Chemical Research 3
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- Robotics and Sensor-Based Localization 3
Raphaël Canals
26 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Plant Science 862
- Analytical Chemistry 205
- Ecology 456
- Environmental Engineering 209
- Media Technology 69
Countries citing papers authored by Raphaël Canals
This map shows the geographic impact of Raphaël Canals'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 Raphaël Canals with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Canals more than expected).
Fields of papers citing papers by Raphaël Canals
This network shows the impact of papers produced by Raphaël Canals. 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 Raphaël Canals. The network helps show where Raphaël Canals may publish in the future.
Co-authorship network
The 16 scholars most cited alongside Raphaël Canals, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 21 | |
| 4 | 2023 | 28 | |
| 5 | 2023 | 6 | |
| 6 | 2022 | 9 | |
| 7 | 2022 | 12 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 6 | |
| 10 | 2022 | 7 | |
| 11 | 2022 | 1 | |
| 12 | Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Researchbreakdown → | 2021 | 159 |
| 13 | Vine disease detection in UAV multispectral images using optimized image registration and deep learning segmentation approachbreakdown → | 2020 | 208 |
| 14 | 2018 | 197 | |
| 15 | 2016 | 51 | |
| 16 | 2013 | 32 | |
| 17 | Occlusion-handling for improved particle filtering-based tracking | 2009 | 2 |
| 18 | A new fast level set method | 2004 | 5 |
| 19 | 1999 | 18 | |
| 20 | 1991 | 1 |
About Raphaël Canals
Raphaël Canals is a scholar working on Biophysics, Analytical Chemistry, Environmental Engineering, Ecology and Plant Science, having authored 27 papers that have together received 1.3k indexed citations. Recurring topics across this work include Smart Agriculture and AI (12 papers), Remote Sensing in Agriculture (9 papers), Diabetic Foot Ulcer Assessment and Management (5 papers), Infrared Thermography in Medicine (5 papers), Remote Sensing and LiDAR Applications (5 papers), Spectroscopy and Chemometric Analyses (4 papers), Spectroscopy Techniques in Biomedical and Chemical Research (3 papers) and Robotics and Sensor-Based Localization (3 papers). The work is most often cited by research in Plant Science (862 citations), Analytical Chemistry (205 citations), Ecology (456 citations), Environmental Engineering (209 citations) and Media Technology (69 citations). Raphaël Canals has collaborated with scholars based in France, Morocco and Peru. Frequent co-authors include Adel Hafiane, Mamadou Dian Bah, Youssef Es-Saady, Mohamed El Hajji, Aladine Chetouani, Sylvie Treuillet, Rachid Harba, Bruno Emile, L. M. Torres and Meryem Jabloun. Their work appears in journals such as Remote Sensing, Computers and Electronics in Agriculture, Expert Systems with Applications, Scientific Reports and IEEE Transactions on Industrial Electronics.
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.