Pablo M. Granitto

3.6k citations
64 papers · 2.6k indexed · 1 hit paper · h-index 23
Topics
Spectroscopy and Chemometric Analyses (16 papers)Advanced Chemical Sensor Technologies (11 papers)Neural Networks and Applications (10 papers)
Journals
Physical Review LettersSHILAP Revista de lepidopterologíaExpert Systems with Applications
Partner nations
ArgentinaItalyAustria

In The Last Decade

Pablo M. Granitto

62 papers receiving 2.5k citations

Hit Papers

Deep learning for plant identification using vein morphol...20162026201920222016100200300400

Peers

Pablo M. Granitto
Comparison fields: 5 of 173
  • Plant Science 1.0k
  • Analytical Chemistry 520
  • Artificial Intelligence 388
  • Biomedical Engineering 341
  • Ecology 319
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Citations per field
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Citations per year

Countries citing papers authored by Pablo M. Granitto

Since Specialization
Citations

This map shows the geographic impact of Pablo M. Granitto'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 Pablo M. Granitto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pablo M. Granitto more than expected).

Fields of papers citing papers by Pablo M. Granitto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pablo M. Granitto. 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 Pablo M. Granitto. The network helps show where Pablo M. Granitto may publish in the future.

Co-authorship network of co-authors of Pablo M. Granitto

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo M. Granitto. A scholar is included among the top collaborators of Pablo M. Granitto 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 Pablo M. Granitto. Pablo M. Granitto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 6
3
Carpyncho: VVV Catalog browser toolkit
1
4 113
5
Generación de features en la búsqueda de estrellas variables en el relevamiento astronómico VVV
1
6 52
7 18
8 30
9 22
10 32
11 41
12 36
13 54
14
Feature selection with simple ANN ensembles
1
15 2
16 17
17
Modeling sensory analysis datasets: the case of Italian cheeses
1
18 129
19
Automatic identification of weed seeds by color image processing
12
20
Frost prediction with machine learning techniques
10

About Pablo M. Granitto

Pablo M. Granitto is a scholar working on Analytical Chemistry, Signal Processing and Instrumentation, having authored 64 papers that have together received 2.6k indexed citations. Recurring topics across this work include Spectroscopy and Chemometric Analyses (16 papers), Advanced Chemical Sensor Technologies (11 papers) and Neural Networks and Applications (10 papers). The work is most often cited by research in Analytical Chemistry (520 citations), Plant Science (1.0k citations) and Food Science (290 citations). Pablo M. Granitto has collaborated with scholars based in Argentina, Italy and Austria. Frequent co-authors include Franco Biasioli, Flavia Gasperi, Mónica G. Larese, Guillermo L. Grinblat, Lucas C. Uzal, P.F. Verdes, H. A. Ceccatto, Cesare Furlanello, H. D. Navone and Luca Cappellin. Their work appears in journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Expert Systems with 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.

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