World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
6195
World Ranking
12032
National Ranking
50

Renato A. Krohling 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 Renato A. Krohling 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: 105 publications — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Renato A. Krohling 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 Renato A. Krohling 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Renato A. Krohling is affiliated with the Universidade Federal do Espírito Santo in Brazil. Their research primarily spans the fields of Computer Science and Medicine, with a particular focus on Artificial Intelligence and its applications.

Their work encompasses a variety of specialized subjects, including:

  • Artificial Intelligence
  • Plant Science
  • Oncology
  • Computer Vision and Pattern Recognition
  • Epidemiology

Key topics addressed in their research are:

  • AI in cancer detection
  • Cutaneous Melanoma Detection and Management
  • Nonmelanoma Skin Cancer Studies
  • Smart Agriculture and AI
  • Digital Imaging for Blood Diseases
  • Oral Health Pathology and Treatment
  • Spectroscopy Techniques in Biomedical and Chemical Research

Renato A. Krohling has contributed to various journals and conferences, with frequent publications in venues such as:

  • arXiv (Cornell University)
  • Computers and Electronics in Agriculture
  • Data in Brief
  • IEEE Journal of Biomedical and Health Informatics
  • Information Processing in Agriculture

Among their recent papers are:

  • Deep learning for classification and severity estimation of coffee leaf biotic stress, 2020, Computers and Electronics in Agriculture
  • An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification, 2021, IEEE Journal of Biomedical and Health Informatics
  • A deep learning approach combining instance and semantic segmentation to identify diseases and pests of coffee leaves from in-field images, 2021, Computers and Electronics in Agriculture
  • An app to assist farmers in the identification of diseases and pests of coffee leaves using deep learning, 2021, Information Processing in Agriculture
  • Few-shot learning for biotic stress classification of coffee leaves, 2022, Artificial Intelligence in Agriculture

Renato A. Krohling frequently collaborates with several researchers, including:

  • Leandro M. de Lima
  • José G. M. Esgario
  • Matheus Becali Rocha
  • Tania R. P. Canuto
  • André G. C. Pacheco

Best Publications

  • Design of optimal disturbance rejection PID controllers using genetic algorithms

    R.A. Krohling;J.P. Rey

  • Fuzzy TOPSIS for group decision making: A case study for accidents with oil spill in the sea

    Renato A. Krohling;Vinicius C. Campanharo

  • Coevolutionary Particle Swarm Optimization Using Gaussian Distribution for Solving Constrained Optimization Problems

    R.A. Krohling;L. dos Santos Coelho

  • Deep learning for classification and severity estimation of coffee leaf biotic stress

    José G.M. Esgario;Renato A. Krohling;José A. Ventura

  • Combining prospect theory and fuzzy numbers to multi-criteria decision making

    Renato A. Krohling;Talles T. M. de Souza

  • Gaussian swarm: a novel particle swarm optimization algorithm

    R.A. Krohling

  • A-TOPSIS – An Approach Based on TOPSIS for Ranking Evolutionary Algorithms☆

    Renato A. Krohling;André G.C. Pacheco

  • An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification

    Andre G. C. Pacheco;Renato A. Krohling

  • Short Communication: IF-TODIM: An intuitionistic fuzzy TODIM to multi-criteria decision making

    Renato A. Krohling;André G. C. Pacheco;André L. T. Siviero

  • The impact of patient clinical information on automated skin cancer detection

    Andre G.C. Pacheco;Renato A. Krohling

  • Co-evolutionary particle swarm optimization to solve min-max problems

    Yuhui Shi;R.A. Krohling

  • Robust Control Systems with Genetic Algorithms

    Mo Jamshidi;Renato A. Krohling;Leandro dos S. Coelho;Peter J. Fleming

  • A study of TODIM in a intuitionistic fuzzy and random environment

    Rodolfo Lourenzutti;Renato A. Krohling

  • A generalized TOPSIS method for group decision making with heterogeneous information in a dynamic environment

    Rodolfo Lourenzutti;Renato A. Krohling

  • A deep learning approach combining instance and semantic segmentation to identify diseases and pests of coffee leaves from in-field images

    Lucas M. Tassis;João E. Tozzi de Souza;Renato A. Krohling

  • Choquet based TOPSIS and TODIM for dynamic and heterogeneous decision making with criteria interaction

    Rodolfo Lourenzutti;Renato A. Krohling;Marek Z. Reformat

  • Designing PI/PID controllers for a motion control system based on genetic algorithms

    R.A. Krohling;H. Jaschek;J.P. Rey

  • PAD-UFES-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones.

    Andre G. C. Pacheco;Gustavo R. Lima;Amanda S. Salomão;Breno A. Krohling

  • Bare Bones Particle Swarm Optimization with Gaussian or Cauchy jumps

    Renato A. Krohling;Eduardo Mendel

  • Gaussian particle swarm with jumps

    R.A. Krohling

  • The Hellinger distance in Multicriteria Decision Making: An illustration to the TOPSIS and TODIM methods

    Rodolfo Lourenzutti;Renato A. Krohling

  • Differential evolution algorithm on the GPU with C-CUDA

    Lucas de P. Veronese;Renato A. Krohling

Frequent Co-Authors

Frank Hoffmann
Frank Hoffmann TU Dortmund University
Leandro dos Santos Coelho
Leandro dos Santos Coelho Federal University of Paraná
Mo Jamshidi
Mo Jamshidi The University of Texas at San Antonio
Peter J. Fleming
Peter J. Fleming University of Sheffield

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