World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5155
World Ranking
10358
National Ranking
312

Fabio Del Frate publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Fabio Del Frate sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 265 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Fabio Del Frate D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Fabio Del Frate sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Fabio Del Frate is affiliated with the University of Rome Tor Vergata in Italy. Their research primarily spans the fields of Environmental Science and Earth and Planetary Sciences, with significant contributions also in several subfields including Atmospheric Science, Global and Planetary Change, Environmental Engineering, Media Technology, and Ecology.

The main topics covered in their work include Meteorological Phenomena and Simulations, Remote-Sensing Image Classification, Remote Sensing in Agriculture, Climate variability and models, Air Quality Monitoring and Forecasting, Remote Sensing and Land Use, and Atmospheric aerosols and clouds.

Fabio Del Frate has published extensively in various scientific journals and conferences, with frequent publications in Remote Sensing, the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, and the IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Other venues include the European Journal of Remote Sensing and arXiv (Cornell University).

Their recent papers include:

  • Artificial intelligence to advance Earth observation:: A review of models, recent trends, and pathways forward, 2023, arXiv (Cornell University)
  • Geometrical Approximated Principal Component Analysis for Hyperspectral Image Analysis, 2020, Remote Sensing
  • Satellite Data Potentialities in Solid Waste Landfill Monitoring: Review and Case Studies, 2023, Sensors
  • Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward, 2024, IEEE Geoscience and Remote Sensing Magazine
  • Deep Learning for Mineral and Biogenic Oil Slick Classification With Airborne Synthetic Aperture Radar Data, 2020, IEEE Transactions on Geoscience and Remote Sensing

Their frequent coauthors include:

  • G. Schiavon
  • Davide De Santis
  • Giorgia Guerrisi
  • Daniele Latini
  • Ilaria Petracca

Best Publications

  • Neural networks for oil spill detection using ERS-SAR data

    Unknown

  • Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data

    Gaia Vaglio Laurin;Gaia Vaglio Laurin;Qi Chen;Jeremy A. Lindsell;David A. Coomes

  • Pixel Unmixing in Hyperspectral Data by Means of Neural Networks

    Unknown

  • Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa

    Gaia Vaglio Laurin;Gaia Vaglio Laurin;Veraldo Liesenberg;Qi Chen;Leila Guerriero

  • Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks

    F Del Frate;P Ferrazzoli;G Schiavon

  • Neural Networks and Support Vector Machine Algorithms for Automatic Cloud Classification of Whole-Sky Ground-Based Images

    Alireza Taravat;Fabio Del Frate;Cristina Cornaro;Stefania Vergari

  • Use of Neural Networks for Automatic Classification From High-Resolution Images

    Unknown

  • Review of Thermal Infrared Applications and Requirements for Future High-Resolution Sensors

    José A. Sobrino;Fabio Del Frate;Matthias Drusch;Juan C. Jiménez-Muñoz

  • An Innovative Neural-Net Method to Detect Temporal Changes in High-Resolution Optical Satellite Imagery

    F. Pacifici;F. Del Frate;C. Solimini;W.J. Emery

  • Urban Mapping Using Coarse SAR and Optical Data: Outcome of the 2007 GRSS Data Fusion Contest

    F. Pacifici;F. Del Frate;W.J. Emery;P. Gamba

  • SAR polarimetric features of agricultural areas

    S. Baronti;F. Del Frate;P. Ferrazzoli;S. Paloscia

  • On the correlation between code coverage and software reliability

    F. Del Frate;P. Garg;A.P. Mathur;A. Pasquini

  • Biodiversity mapping in a tropical West African forest with airborne hyperspectral data.

    Gaia Vaglio Laurin;Jonathan Cheung-Wai Chan;Qi Chen;Jeremy A. Lindsell

  • Automatic Change Detection in Very High Resolution Images With Pulse-Coupled Neural Networks

    Unknown

  • A combined natural orthogonal functions/neural network technique for the radiometric estimation of atmospheric profiles

    Fabio Del Frate;Giovanni Schiavon

  • Transport Infrastructure Monitoring by InSAR and GPR Data Fusion

    Luca Bianchini Ciampoli;Valerio Gagliardi;Chiara Clementini;Daniele Latini

  • Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking

    Alireza Taravat;Simon Richard Proud;Simone Peronaci;Fabio Del Frate

  • Comparing Statistical and Neural Network Methods Applied to Very High Resolution Satellite Images Showing Changes in Man-Made Structures at Rocky Flats

    M. Chini;F. Pacifici;W.J. Emery;N. Pierdicca

  • Monitoring Urban Land Cover in Rome, Italy, and Its Changes by Single-Polarization Multitemporal SAR Images

    Unknown

  • Wheat cycle monitoring using radar data and a neural network trained by a model

    F. Del Frate;P. Ferrazzoli;L. Guerriero;T. Strozzi

  • A neural network approach for the simultaneous retrieval of volcanic ash parameters and SO 2 using MODIS data

    Alessandro Piscini;M. Picchiani;M. Chini;Stefano Corradini

  • Fully Automatic Dark-Spot Detection From SAR Imagery With the Combination of Nonadaptive Weibull Multiplicative Model and Pulse-Coupled Neural Networks

    Alireza Taravat;Daniele Latini;Fabio Del Frate

  • Nonlinear Spectral Unmixing of Landsat Imagery for Urban Surface Cover Mapping

    Zina Mitraka;Fabio Del Frate;Francesco Carbone

  • Development of band ratioing algorithms and neural networks to detection of oil spills using Landsat ETM+ data

    Alireza Taravat;Fabio Del Frate

  • Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images

    L. Pasolli;C. Notarnicola;L. Bruzzone;G. Bertoldi

  • Hyperspectral and Multiangle CHRIS-PROBA Images for the Generation of Land Cover Maps

    Riccardo Duca;Fabio Del Frate

Frequent Co-Authors

Nektarios Chrysoulakis
Nektarios Chrysoulakis Foundation for Research and Technology Hellas
Fredrik Lindberg
Fredrik Lindberg University of Gothenburg
Jean-Philippe Gastellu-Etchegorry
Jean-Philippe Gastellu-Etchegorry Federal University of Toulouse Midi-Pyrénées
Salvatore Stramondo
Salvatore Stramondo National Institute of Geophysics and Volcanology
Roy G. Grainger
Roy G. Grainger University of Oxford
Marco Chini
Marco Chini National Institute of Geophysics and Volcanology
Riccardo Valentini
Riccardo Valentini Tuscia University
Claudia Notarnicola
Claudia Notarnicola European Academy of Bozen
Ahmad Al Bitar
Ahmad Al Bitar Federal University of Toulouse Midi-Pyrénées
William J. Emery
William J. Emery University of Colorado Boulder

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