Ribana Roscher
- Artificial Intelligence top 2%
- Plant Science top 5%
- Ecology top 5%
- Environmental Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Jochen GarckeMarco F. DuarteBastian BohnBjörn WaskeAnna KichererWen YangAnna KruspeJianxiang Feng
- Topics
- Remote Sensing in Agriculture (21 papers)Smart Agriculture and AI (16 papers)Remote-Sensing Image Classification (16 papers)
- Journals
- SHILAP Revista de lepidopterologíaRemote Sensing of EnvironmentIEEE Transactions on Geoscience and Remote Sensing
- Partner nations
- GermanyUnited KingdomChina
In The Last Decade
Ribana Roscher
64 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 165
- Artificial Intelligence 558
- Plant Science 371
- Ecology 317
- Environmental Engineering 271
- Computer Vision and Pattern Recognition 201
Countries citing papers authored by Ribana Roscher
This map shows the geographic impact of Ribana Roscher'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 Ribana Roscher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ribana Roscher more than expected).
Fields of papers citing papers by Ribana Roscher
This network shows the impact of papers produced by Ribana Roscher. 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 Ribana Roscher. The network helps show where Ribana Roscher may publish in the future.
Co-authorship network of co-authors of Ribana Roscher
This figure shows the co-authorship network connecting the top 25 collaborators of Ribana Roscher. A scholar is included among the top collaborators of Ribana Roscher based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ribana Roscher. Ribana Roscher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 10 | |
| 5 | 15 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | A survey of uncertainty in deep neural networksbreakdown → | 509 |
| 9 | 6 | |
| 10 | 3 | |
| 11 | 16 | |
| 12 | 23 | |
| 13 | 8 | |
| 14 | 32 | |
| 15 | 17 | |
| 16 | 1 | |
| 17 | 9 | |
| 18 | 34 | |
| 19 | 16 | |
| 20 | 4 |
About Ribana Roscher
Ribana Roscher is a scholar working on Media Technology, Environmental Engineering and Ecology, having authored 70 papers that have together received 2.0k indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (21 papers), Smart Agriculture and AI (16 papers) and Remote-Sensing Image Classification (16 papers). The work is most often cited by research in Health Informatics (42 citations), Media Technology (189 citations) and Environmental Engineering (271 citations). Ribana Roscher has collaborated with scholars based in Germany, United Kingdom and China. Frequent co-authors include Jochen Garcke, Marco F. Duarte, Bastian Bohn, Björn Waske, Anna Kicherer, Wen Yang, Anna Kruspe, Jianxiang Feng, Richard Bamler and Peter Jung. Their work appears in journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and IEEE Transactions on Geoscience 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.