World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
58
Citations
16290
World Ranking
3576
National Ranking
1719

M. Emre Celebi 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 M. Emre Celebi 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: 187 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

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

M. Emre Celebi 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 M. Emre Celebi 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

M. Emre Celebi is affiliated with the University of Central Arkansas in the United States. The primary fields of study for this researcher are Computer Science and Medicine, with significant contributions in subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Oncology, Media Technology, and Biomedical Engineering.

The scientist's work covers a range of main topics including Cutaneous Melanoma Detection and Management, AI in cancer detection, Advanced Image Fusion Techniques, Digital Media Forensic Detection, Advanced Data Compression Techniques, Advanced Image and Video Retrieval Techniques, and Image Retrieval and Classification Techniques.

Recent publications authored or co-authored by M. Emre Celebi include the following:

  • Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects (2021), published in Information Fusion
  • A survey on deep learning for skin lesion segmentation (2023), published in Medical Image Analysis
  • Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology (2021), published in JAMA Dermatology
  • Explainable skin lesion diagnosis using taxonomies (2020), published in Pattern Recognition
  • The incremental online k-means clustering algorithm and its application to color quantization (2022), published in Expert Systems with Applications

M. Emre Celebi frequently collaborates with several co-authors, including Catarina Barata, Marc Combalia, Allan C. Halpern, Philipp Tschandl, and Pourya Shamsolmoali.

The researcher has published multiple papers in recognized venues, with frequent contributions to the IEEE Journal of Biomedical and Health Informatics, Information Fusion, Medical Image Analysis, Journal of Electronic Imaging, and JAMA Dermatology.

In addition to journal articles, M. Emre Celebi has authored a book titled Deep Learning for Security and Privacy Preservation in IoT, published by Springer Vienna in 2021.

Best Publications

  • Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC)

    Noel C. F. Codella;David Gutman;M. Emre Celebi;Brian Helba

  • A comparative study of efficient initialization methods for the k-means clustering algorithm

    M. Emre Celebi;Hassan A. Kingravi;Patricio A. Vela

  • Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)

    Noel C. F. Codella;Veronica Rotemberg;Philipp Tschandl;M. Emre Celebi

  • A Methodological Approach to the Classification of Dermoscopy Images

    M. Emre Celebi;Hassan A. Kingravi;Bakhtiyar Uddin;Hitoshi Iyatomi

  • Lesion border detection in dermoscopy images.

    M.Emre Celebi;Hitoshi Iyatomi;Gerald Schaefer;William V. Stoecker

  • Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images

    Michael A. Marchetti;Noel C.F. Codella;Stephen W. Dusza;David A. Gutman

  • Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)

    Noel C. F. Codella;David Gutman;M. Emre Celebi;Brian Helba

  • Border detection in dermoscopy images using statistical region merging.

    M. Emre Celebi;Hassan A. Kingravi;Hitoshi Iyatomi;Y. Alp Aslandogan

  • Unsupervised Learning Algorithms

    M. Emre Celebi;Kemal Aydin

  • An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm

    Hitoshi Iyatomi;Hitoshi Iyatomi;Hiroshi Oka;M.Emre Celebi;Masahiro Hashimoto

  • Lesion Border Detection in Dermoscopy Images Using Ensembles of Thresholding Methods

    M. Emre Celebi;Quan Wen;Sae Hwang;Hitoshi Iyatomi

  • Improving Dermoscopy Image Classification Using Color Constancy

    Catarina Barata;M. Emre Celebi;Jorge S. Marques

  • Improving the performance of k-means for color quantization

    M. Emre Celebi

  • Anisotropic Mean Shift Based Fuzzy C-Means Segmentation of Dermoscopy Images

    Huiyu Zhou;G. Schaefer;A.H. Sadka;M.E. Celebi

  • Unsupervised border detection in dermoscopy images

    M. Emre Celebi;Y. Alp Aslandogan;William V. Stoecker;Hitoshi Iyatomi

  • Advances in Data Preprocessing for Biomedical Data Fusion: An Overview of the Methods, Challenges, and Prospects

    Shuihua Wang;M. Emre Celebi;Yu-Dong Zhang;Xiang Yu

  • A Survey of Feature Extraction in Dermoscopy Image Analysis of Skin Cancer

    Catarina Barata;M. Emre Celebi;Jorge S. Marques

  • Automatic detection of blue-white veil and related structures in dermoscopy images

    M. Emre Celebi;Hitoshi Iyatomi;William V. Stoecker;Randy H. Moss

  • Border detection in dermoscopy images using hybrid thresholding on optimized color channels.

    Rahil Garnavi;Mohammad Aldeen;M. Emre Celebi;George Varigos

  • Partitional Clustering Algorithms

    M. Emre Celebi

  • Dermoscopy Image Analysis: Overview and Future Directions

    M. Emre Celebi;Noel Codella;Allan Halpern

Frequent Co-Authors

Gerald Schaefer
Gerald Schaefer Loughborough University
William V. Stoecker
William V. Stoecker Missouri University of Science and Technology
Jorge S. Marques
Jorge S. Marques Instituto Superior Técnico
Huiyu Zhou
Huiyu Zhou University of Leicester
Randy Hays Moss
Randy Hays Moss Missouri University of Science and Technology
Allan C. Halpern
Allan C. Halpern Memorial Sloan Kettering Cancer Center
Ashfaq A. Marghoob
Ashfaq A. Marghoob Memorial Sloan Kettering Cancer Center
H. Peter Soyer
H. Peter Soyer University of Queensland
Giuseppe Argenziano
Giuseppe Argenziano University of Campania "Luigi Vanvitelli"
Ahmed Bouridane
Ahmed Bouridane University of Sharjah

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