Charles‐Alban Deledalle

About

Charles‐Alban Deledalle is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Charles‐Alban Deledalle has authored 42 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 17 papers in Computational Mechanics and 12 papers in Aerospace Engineering. Recurrent topics in Charles‐Alban Deledalle’s work include Image and Signal Denoising Methods (26 papers), Sparse and Compressive Sensing Techniques (17 papers) and Advanced Image Processing Techniques (11 papers). Charles‐Alban Deledalle is often cited by papers focused on Image and Signal Denoising Methods (26 papers), Sparse and Compressive Sensing Techniques (17 papers) and Advanced Image Processing Techniques (11 papers). Charles‐Alban Deledalle collaborates with scholars based in France, United States and Italy. Charles‐Alban Deledalle's co-authors include Laurent Denis, Florence Tupin, Jean–François Aujol, Samuel Vaiter and Giampaolo Ferraioli and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and The Journal of the Acoustical Society of America.

In The Last Decade

Fields of papers citing papers by Charles‐Alban Deledalle

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 Charles‐Alban Deledalle. Nodes represent fields, and links connect fields that are likely to share authors. The network helps show where Charles‐Alban Deledalle may publish in the future.

Countries citing papers authored by Charles‐Alban Deledalle

Since Specialization

Citations

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

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