Valeria Tomaselli
- Plant Science
- Computer Vision and Pattern Recognition top 10%
- Analytical Chemistry top 10%
- Electrical and Electronic Engineering
- Artificial Intelligence
- Co-authors
- Danilo PauClaudio TurchettiLaura FalaschettiSebastiano BattiatoFabrizio De VitaGiovanni Maria FarinellaDario BruneoSajal K. Das
- Topics
- Image and Signal Denoising Methods (5 papers)Smart Agriculture and AI (5 papers)Advanced Image and Video Retrieval Techniques (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaPattern RecognitionMultimedia Tools and Applications
- Partner nations
- ItalySwitzerlandUnited States
In The Last Decade
Valeria Tomaselli
30 papers receiving 306 citations
Peers
Comparison fields: 5 of 62
- Plant Science 160
- Computer Vision and Pattern Recognition 77
- Analytical Chemistry 45
- Electrical and Electronic Engineering 27
- Artificial Intelligence 26
Countries citing papers authored by Valeria Tomaselli
This map shows the geographic impact of Valeria Tomaselli'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 Valeria Tomaselli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Valeria Tomaselli more than expected).
Fields of papers citing papers by Valeria Tomaselli
This network shows the impact of papers produced by Valeria Tomaselli. 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 Valeria Tomaselli. The network helps show where Valeria Tomaselli may publish in the future.
Co-authorship network of co-authors of Valeria Tomaselli
This figure shows the co-authorship network connecting the top 25 collaborators of Valeria Tomaselli. A scholar is included among the top collaborators of Valeria Tomaselli 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 Valeria Tomaselli. Valeria Tomaselli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 7 | |
| 3 | 46 | |
| 4 | 15 | |
| 5 | 36 | |
| 6 | 30 | |
| 7 | 12 | |
| 8 | 27 | |
| 9 | 2 | |
| 10 | 6 | |
| 11 | 21 | |
| 12 | 28 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | 32 | |
| 19 | 3 | |
| 20 | 1 |
About Valeria Tomaselli
Valeria Tomaselli is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Human-Computer Interaction, having authored 30 papers that have together received 321 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (5 papers), Smart Agriculture and AI (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Analytical Chemistry (45 citations), Plant Science (160 citations) and Computer Vision and Pattern Recognition (77 citations). Valeria Tomaselli has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include Danilo Pau, Claudio Turchetti, Laura Falaschetti, Sebastiano Battiato, Fabrizio De Vita, Giovanni Maria Farinella, Dario Bruneo, Sajal K. Das, Davide Giacalone and Arcangelo Bruna. Their work appears in journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Multimedia Tools and Applications.
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.