World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
8853
World Ranking
6497
National Ranking
151

Giovanni Poggi 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 Giovanni Poggi 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: 175 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Giovanni Poggi 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 Giovanni Poggi 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Giovanni Poggi is affiliated with the University of Naples Federico II in Italy. Their research primarily centers in the fields of Computer Science and Engineering, with a focus on subfields such as Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, and Biomedical Engineering.

Their work spans several main topics including Digital Media Forensic Detection, Advanced Image Fusion Techniques, Generative Adversarial Networks and Image Synthesis, Advanced Steganography and Watermarking Techniques, Advanced Image Processing Techniques, Image and Signal Denoising Methods, and Spectroscopy Techniques in Biomedical and Chemical Research.

Giovanni Poggi has published extensively, contributing to various journals and conference proceedings. Notable recent papers include:

  • Nonlocal CNN SAR Image Despeckling (2020), published in Remote Sensing
  • Unsupervised Deep Learning-Based Pansharpening With Jointly Enhanced Spectral and Spatial Fidelity (2023), published in IEEE Transactions on Geoscience and Remote Sensing
  • Towards Universal GAN Image Detection (2021), presented at the 2021 International Conference on Visual Communications and Image Processing (VCIP)
  • PCA-CNN Hybrid Approach for Hyperspectral Pansharpening (2023), published in IEEE Geoscience and Remote Sensing Letters
  • Hyperspectral Pansharpening: Critical review, tools, and future perspectives (2024), published in IEEE Geoscience and Remote Sensing Magazine

Their collaborative network includes frequent co-authors such as Luisa Verdoliva, Davide Cozzolino, Giuseppe Scarpa, Diego Gragnaniello, and Riccardo Corvi. The number of joint publications with these co-authors ranges from eight up to twenty-three.

Giovanni Poggi's research output is often published in venues like arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, and IEEE Geoscience and Remote Sensing Magazine.

Best Publications

  • Land Use Classification in Remote Sensing Images by Convolutional Neural Networks

    Marco Castelluccio;Giovanni Poggi;Carlo Sansone;Luisa Verdoliva

  • Efficient Dense-Field Copy–Move Forgery Detection

    Davide Cozzolino;Giovanni Poggi;Luisa Verdoliva

  • Compression of multispectral images by three-dimensional SPIHT algorithm

    P. Luigi Dragotti;G. Poggi;A.R.P. Ragozini

  • Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection

    Davide Cozzolino;Giovanni Poggi;Luisa Verdoliva

  • Do GANs Leave Artificial Fingerprints

    Francesco Marra;Diego Gragnaniello;Luisa Verdoliva;Giovanni Poggi

  • SAR image despeckling through convolutional neural networks

    G. Chierchia;D. Cozzolino;G. Poggi;L. Verdoliva

  • Splicebuster: A new blind image splicing detector

    Davide Cozzolino;Giovanni Poggi;Luisa Verdoliva

  • A Bayesian-MRF Approach for PRNU-Based Image Forgery Detection

    Giovanni Chierchia;Giovanni Poggi;Carlo Sansone;Luisa Verdoliva

  • Fast Adaptive Nonlocal SAR Despeckling

    Davide Cozzolino;Sara Parrilli;Giuseppe Scarpa;Giovanni Poggi

  • An Investigation of Local Descriptors for Biometric Spoofing Detection

    Diego Gragnaniello;Giovanni Poggi;Carlo Sansone;Luisa Verdoliva

  • A tree-structured Markov random field model for Bayesian image segmentation

    C. D'Elia;G. Poggi;G. Scarpa

  • Exploiting Patch Similarity for SAR Image Processing: The nonlocal paradigm

    Charles-Alban Deledalle;Loic Denis;Giovanni Poggi;Florence Tupin

  • Benchmarking Framework for SAR Despeckling

    Gerardo Di Martino;Mariana Poderico;Giovanni Poggi;Daniele Riccio

  • Fingerprint liveness detection based on Weber Local image Descriptor

    Diego Gragnaniello;Giovanni Poggi;Carlo Sansone;Luisa Verdoliva

  • Deep Learning Methods For Synthetic Aperture Radar Image Despeckling: An Overview Of Trends And Perspectives

    Giulia Fracastoro;Enrico Magli;Giovanni Poggi;Giuseppe Scarpa

  • Local contrast phase descriptor for fingerprint liveness detection

    Diego Gragnaniello;Giovanni Poggi;Carlo Sansone;Luisa Verdoliva

  • Copy-move forgery detection based on PatchMatch

    Davide Cozzolino;Giovanni Poggi;Luisa Verdoliva

  • Marker-Controlled Watershed-Based Segmentation of Multiresolution Remote Sensing Images

    Raffaele Gaetano;Giuseppe Masi;Giovanni Poggi;Luisa Verdoliva

  • A PatchMatch-Based Dense-Field Algorithm for Video Copy–Move Detection and Localization

    Luca D'Amiano;Davide Cozzolino;Giovanni Poggi;Luisa Verdoliva

  • Autoencoder with recurrent neural networks for video forgery detection

    Dario D'Avino;Davide Cozzolino;Giovanni Poggi;Luisa Verdoliva

  • Supervised segmentation of remote sensing images based on a tree-structured MRF model

    G. Poggi;G. Scarpa;J.B. Zerubia

  • Are GAN Generated Images Easy to Detect? A Critical Analysis of the State-Of-The-Art

    Diego Gragnaniello;Davide Cozzolino;Francesco Marra;Giovanni Poggi

Frequent Co-Authors

Luisa Verdoliva
Luisa Verdoliva University of Naples Federico II
Davide Cozzolino
Davide Cozzolino University of Naples Federico II
Carlo Sansone
Carlo Sansone University of Naples Federico II
Daniele Riccio
Daniele Riccio University of Naples Federico II
Josiane Zerubia
Josiane Zerubia French Institute for Research in Computer Science and Automation - INRIA
Sebastiano B. Serpico
Sebastiano B. Serpico University of Genoa
Gianfranco Fornaro
Gianfranco Fornaro National Research Council (CNR)
Gabriele Moser
Gabriele Moser University of Genoa
Fabio Roli
Fabio Roli University of Genoa
Florence Tupin
Florence Tupin Télécom ParisTech

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Related Online Degrees & Career Pathways

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