Paolo Garza
- Artificial Intelligence top 2%
- Information Systems top 1%
- Computational Theory and Mathematics top 2%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Elena BaralisLuca CaglieroTania CerquitelliSilvia ChiusanoAlessandro FarasinDaniele ApilettiElisa QuintarelliAlessandro Fiori
- Topics
- Data Mining Algorithms and Applications (38 papers)Data Management and Algorithms (19 papers)Rough Sets and Fuzzy Logic (15 papers)
- Journals
- Expert Systems with ApplicationsInformation SciencesIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- ItalyUnited StatesFrance
In The Last Decade
Paolo Garza
104 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 492
- Information Systems 477
- Computational Theory and Mathematics 237
- Signal Processing 176
- Computer Networks and Communications 160
Countries citing papers authored by Paolo Garza
This map shows the geographic impact of Paolo Garza'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 Paolo Garza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paolo Garza more than expected).
Fields of papers citing papers by Paolo Garza
This network shows the impact of papers produced by Paolo Garza. 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 Paolo Garza. The network helps show where Paolo Garza may publish in the future.
Co-authorship network of co-authors of Paolo Garza
This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Garza. A scholar is included among the top collaborators of Paolo Garza 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 Paolo Garza. Paolo Garza is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 18 | |
| 9 | 1 | |
| 10 | 7 | |
| 11 | 21 | |
| 12 | Double-Step deep learning framework to improve wildfire severity classification. | 3 |
| 13 | 1 | |
| 14 | 8 | |
| 15 | 9 | |
| 16 | Unsupervised Burned Area Estimation through Satellite Tiles: A multimodal approach by means of image segmentation over remote sensing imagery | 3 |
| 17 | Adaptive Hierarchical Clustering for Petrographic Image Analysis. | 1 |
| 18 | Identifying collaborations among researchers: a pattern-based approach | 3 |
| 19 | Top-N recommendations on Unpopular Items with Contextual Knowledge | 10 |
| 20 | DALLAS HIGH FIVE : A VITAL ECONOMIC LINK FOR NORTH TEXAS | 1 |
About Paolo Garza
Paolo Garza is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 111 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (38 papers), Data Management and Algorithms (19 papers) and Rough Sets and Fuzzy Logic (15 papers). The work is most often cited by research in Information Systems (477 citations), Signal Processing (176 citations) and Artificial Intelligence (492 citations). Paolo Garza has collaborated with scholars based in Italy, United States and France. Frequent co-authors include Elena Baralis, Luca Cagliero, Tania Cerquitelli, Silvia Chiusano, Alessandro Farasin, Daniele Apiletti, Elisa Quintarelli, Alessandro Fiori, Giulia Bruno and Claudio Rossi. Their work appears in journals such as Expert Systems with Applications, Information Sciences and IEEE Transactions on Intelligent Transportation Systems.
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.