Daniele Cerra

150 total papers · 1.3k total citations
84 papers, 963 citations indexed

About

Daniele Cerra is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Daniele Cerra has authored 84 papers receiving a total of 963 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Media Technology, 24 papers in Computer Vision and Pattern Recognition and 24 papers in Artificial Intelligence. Recurrent topics in Daniele Cerra's work include Remote-Sensing Image Classification (39 papers), Advanced Image Fusion Techniques (23 papers) and Remote Sensing in Agriculture (16 papers). Daniele Cerra is often cited by papers focused on Remote-Sensing Image Classification (39 papers), Advanced Image Fusion Techniques (23 papers) and Remote Sensing in Agriculture (16 papers). Daniele Cerra collaborates with scholars based in Germany, France and United States. Daniele Cerra's co-authors include Peter Reinartz, Mihai Datcu, Rupert Müller, E. Carmona, Miguel Pato, Ronny Hänsch, Naoto Yokoya, Bertrand Le Saux, Liangpei Zhang and Bo Du and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Sensors.

In The Last Decade

Daniele Cerra

80 papers receiving 926 citations

Hit Papers

Advanced Multi-Sensor Opt... 2019 2026 2021 2023 2019 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Daniele Cerra 478 266 196 188 162 84 963
Li Zhang 262 0.5× 275 1.0× 120 0.6× 92 0.5× 131 0.8× 60 997
Emmett J. Ientilucci 552 1.2× 137 0.5× 172 0.9× 132 0.7× 150 0.9× 76 826
V. A. Knyaz 383 0.8× 314 1.2× 177 0.9× 86 0.5× 261 1.6× 86 902
Farzaneh Dadrass Javan 342 0.7× 253 1.0× 182 0.9× 64 0.3× 104 0.6× 58 890
Oğuz Güngör 403 0.8× 219 0.8× 383 2.0× 91 0.5× 143 0.9× 50 1.1k
Mahdi Khodadadzadeh 816 1.7× 209 0.8× 147 0.8× 343 1.8× 422 2.6× 51 1.2k
Chandi Witharana 230 0.5× 112 0.4× 229 1.2× 66 0.4× 351 2.2× 52 897
Xu Huang 391 0.8× 222 0.8× 181 0.9× 66 0.4× 262 1.6× 47 817
Shiyong Cui 564 1.2× 354 1.3× 136 0.7× 116 0.6× 230 1.4× 50 1.1k
Kaimin Sun 444 0.9× 208 0.8× 251 1.3× 60 0.3× 267 1.6× 63 798

Countries citing papers authored by Daniele Cerra

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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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.

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