Roberto Rigamonti

About

Roberto Rigamonti is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Roberto Rigamonti has authored 7 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Computational Mechanics and 2 papers in Artificial Intelligence. Recurrent topics in Roberto Rigamonti’s work include Sparse and Compressive Sensing Techniques (4 papers), Image and Signal Denoising Methods (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Roberto Rigamonti is often cited by papers focused on Sparse and Compressive Sensing Techniques (4 papers), Image and Signal Denoising Methods (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Roberto Rigamonti collaborates with scholars based in Switzerland, United Kingdom and France. Roberto Rigamonti's co-authors include Vincent Lepetit, Pascal Fua, Amos Sironi, Matthew A. Brown and Davide Migliore and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Vision and Image Understanding and Lecture notes in computer science.

In The Last Decade

Fields of papers citing papers by Roberto Rigamonti

Since Specialization

EngineeringComputer SciencePhysics and AstronomyMathematicsEarth and Planetary SciencesEnergyEnvironmental ScienceMaterials ScienceChemical EngineeringChemistryAgricultural and Biological SciencesVeterinaryDecision SciencesArts and HumanitiesBusiness, Management and AccountingSocial SciencesPsychologyEconomics, Econometrics and FinanceHealth ProfessionsDentistryMedicineBiochemistry, Genetics and Molecular BiologyNeuroscienceNursingImmunology and MicrobiologyPharmacology, Toxicology and Pharmaceutics

This network shows the specialization of papers citing the papers produced by Roberto Rigamonti. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Roberto Rigamonti may publish in the future.

Countries citing papers authored by Roberto Rigamonti

Since Specialization

Citations

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

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