H. D. Navone
- Plant Science
- Astronomy and Astrophysics top 10%
- Artificial Intelligence
- Analytical Chemistry top 5%
- Environmental Engineering top 10%
- Co-authors
- H. A. CeccattoPablo M. GranittoP.F. VerdesG. I. PerrenGuillermo H. KaufmannR. VázquezA. MoitinhoJ. C. Muzzio
- Topics
- Stellar, planetary, and galactic studies (7 papers)Neural Networks and Applications (7 papers)Time Series Analysis and Forecasting (6 papers)
- Journals
- Physical Review LettersSHILAP Revista de lepidopterologíaMonthly Notices of the Royal Astronomical Society
In The Last Decade
H. D. Navone
24 papers receiving 413 citations
Peers
Comparison fields: 5 of 82
- Plant Science 106
- Astronomy and Astrophysics 98
- Artificial Intelligence 91
- Analytical Chemistry 78
- Environmental Engineering 73
Countries citing papers authored by H. D. Navone
This map shows the geographic impact of H. D. Navone'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 H. D. Navone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. D. Navone more than expected).
Fields of papers citing papers by H. D. Navone
This network shows the impact of papers produced by H. D. Navone. 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 H. D. Navone. The network helps show where H. D. Navone may publish in the future.
Co-authorship network of co-authors of H. D. Navone
This figure shows the co-authorship network connecting the top 25 collaborators of H. D. Navone. A scholar is included among the top collaborators of H. D. Navone 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 H. D. Navone. H. D. Navone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 21 | |
| 2 | 11 | |
| 3 | 41 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 8 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 111 | |
| 11 | 12 | |
| 12 | 16 | |
| 13 | 36 | |
| 14 | 7 | |
| 15 | Automatic identification of weed seeds by color image processing | 12 |
| 16 | Frost prediction with machine learning techniques | 10 |
| 17 | 2 | |
| 18 | 11 | |
| 19 | 7 | |
| 20 | 2 |
About H. D. Navone
H. D. Navone is a scholar working on Instrumentation, Signal Processing and Astronomy and Astrophysics, having authored 29 papers that have together received 478 indexed citations. Recurring topics across this work include Stellar, planetary, and galactic studies (7 papers), Neural Networks and Applications (7 papers) and Time Series Analysis and Forecasting (6 papers). The work is most often cited by research in Instrumentation (51 citations), Analytical Chemistry (78 citations) and Astronomy and Astrophysics (98 citations). H. D. Navone has collaborated with scholars based in Argentina, Russia and Mexico. Frequent co-authors include H. A. Ceccatto, Pablo M. Granitto, P.F. Verdes, G. I. Perren, Guillermo H. Kaufmann, R. Vázquez, A. Moitinho, J. C. Muzzio, Rubén D. Piacentini and D. D. Carpintero. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Monthly Notices of the Royal Astronomical Society.
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.