Daniele Cerra
- Media Technology top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Ecology top 10%
- Artificial Intelligence top 10%
- Atmospheric Science top 10%
- Co-authors
- Peter ReinartzMihai DatcuRupert MüllerE. CarmonaNaoto YokoyaRonny HänschBertrand Le SauxMiguel Pato
- Topics
- Remote-Sensing Image Classification (40 papers)Advanced Image Fusion Techniques (23 papers)Remote Sensing in Agriculture (16 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Geoscience and Remote SensingSensors
- Partner nations
- GermanyFranceUnited States
In The Last Decade
Daniele Cerra
80 papers receiving 937 citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Media Technology 480
- Computer Vision and Pattern Recognition 267
- Ecology 197
- Artificial Intelligence 189
- Atmospheric Science 163
Countries citing papers authored by Daniele Cerra
This map shows the geographic impact of Daniele Cerra'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 Daniele Cerra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniele Cerra more than expected).
Fields of papers citing papers by Daniele Cerra
This network shows the impact of papers produced by Daniele Cerra. 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 Daniele Cerra. The network helps show where Daniele Cerra may publish in the future.
Co-authorship network of co-authors of Daniele Cerra
This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Cerra. A scholar is included among the top collaborators of Daniele Cerra 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 Daniele Cerra. Daniele Cerra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 8 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 20 | |
| 12 | Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contestbreakdown → | 255 |
| 13 | 36 | |
| 14 | 17 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | 3 | |
| 18 | 21 | |
| 19 | 3 | |
| 20 | 2 |
About Daniele Cerra
Daniele Cerra is a scholar working on Space and Planetary Science, Media Technology and Computer Vision and Pattern Recognition, having authored 85 papers that have together received 974 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (40 papers), Advanced Image Fusion Techniques (23 papers) and Remote Sensing in Agriculture (16 papers). The work is most often cited by research in Space and Planetary Science (72 citations), Media Technology (480 citations) and Geology (84 citations). Daniele Cerra has collaborated with scholars based in Germany, France and United States. Frequent co-authors include Peter Reinartz, Mihai Datcu, Rupert Müller, E. Carmona, Naoto Yokoya, Ronny Hänsch, Bertrand Le Saux, Miguel Pato, Bo Du and Yonghao Xu. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Sensors.
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.