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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
23679
World Ranking
1272
National Ranking
34

Dagan Feng 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 Dagan Feng 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: 705 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

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

Dagan Feng 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 Dagan Feng 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: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Dagan Feng is affiliated with the University of Sydney in Australia. Their research primarily intersects the fields of Medicine and Computer Science, with a notable concentration on Radiology, Nuclear Medicine and Imaging, as well as subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, and Pulmonary and Respiratory Medicine.

Their publication record includes frequent contributions to several scholarly venues. Notably, Dagan Feng has published extensively in:

  • arXiv (Cornell University)
  • IEEE Journal of Biomedical and Health Informatics
  • IEEE Transactions on Medical Imaging
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Industrial Informatics

The main research topics addressed by their work include:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • Medical Imaging Techniques and Applications
  • Medical Image Segmentation Techniques
  • Advanced Neural Network Applications
  • Medical Imaging and Analysis
  • Lung Cancer Diagnosis and Treatment

Dagan Feng has collaborated frequently with several co-authors in the field. The most frequent collaborators are:

  • Jinman Kim (66 joint publications)
  • Lei Bi (43 joint publications)
  • Michael Fulham (30 joint publications)
  • Mingyuan Meng (24 joint publications)
  • Bin Sheng (16 joint publications)

Among their recent publications are:

  • "EAPT: Efficient Attention Pyramid Transformer for Image Processing," 2021, IEEE Transactions on Multimedia
  • "Automatic Detection and Classification System of Domestic Waste via Multimodel Cascaded Convolutional Neural Network," 2021, IEEE Transactions on Industrial Informatics
  • "A Residual Based Attention Model for EEG Based Sleep Staging," 2020, IEEE Journal of Biomedical and Health Informatics
  • "OFF-eNET: An Optimally Fused Fully End-to-End Network for Automatic Dense Volumetric 3D Intracranial Blood Vessels Segmentation," 2020, IEEE Transactions on Image Processing
  • "Automated Decision Support System for Lung Cancer Detection and Classification via Enhanced RFCN With Multilayer Fusion RPN," 2020, IEEE Transactions on Industrial Informatics

Best Publications

  • Medical image classification with convolutional neural network

    Qing Li;Weidong Cai;Xiaogang Wang;Yun Zhou

  • Accelerating magnetic resonance imaging via deep learning

    Shanshan Wang;Zhenghang Su;Leslie Ying;Xi Peng

  • Fundamentals of Content-Based Image Retrieval

    Fuhui Long;Hongjiang Zhang;David Dagan Feng

  • Early diagnosis of Alzheimer's disease with deep learning

    Siqi Liu;Sidong Liu;Weidong Cai;Sonia Pujol

  • Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease

    Siqi Liu;Sidong Liu;Weidong Cai;Hangyu Che

  • Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT

    Yutong Xie;Yong Xia;Jianpeng Zhang;Yang Song

  • EAPT: Efficient Attention Pyramid Transformer for Image Processing

    Xiao Lin;Shuzhou Sun;Wei Huang;Bin Sheng

  • Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer

    Ashnil Kumar;Michael Fulham;Dagan Feng;Jinman Kim

  • Noninvasive Quantification of the Cerebral Metabolic Rate for Glucose Using Positron Emission Tomography, 18F-Fluoro-2-Deoxyglucose, the Patlak Method, and an Image-Derived Input Function

    Kewei Chen;Kewei Chen;Daniel Bandy;Eric Reiman;Sung-Cheng Huang

  • Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks

    Lei Bi;Jinman Kim;Euijoon Ahn;Ashnil Kumar

  • Models for computer simulation studies of input functions for tracer kinetic modeling with positron emission tomography

    Dagan Feng;Sung-Cheng Huang;Xinmin Wang

  • Computer-Assisted Decision Support System in Pulmonary Cancer detection and stage classification on CT images

    Anum Masood;Bin Sheng;Ping Li;Xuhong Hou

  • Robust saliency detection via regularized random walks ranking

    Changyang Li;Yuchen Yuan;Weidong Cai;Yong Xia

  • Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.

    Ashnil Kumar;Jinman Kim;Weidong Cai;Michael J. Fulham;Michael J. Fulham

  • Automatic Detection and Classification System of Domestic Waste via Multimodel Cascaded Convolutional Neural Network

    Jiajia Li;Jie Chen;Bin Sheng;Ping Li

  • Segmentation of dynamic PET images using cluster analysis

    Koon-Pong Wong;Dagan Feng;S.R. Meikle;M.J. Fulham

  • A technique for extracting physiological parameters and the required input function simultaneously from PET image measurements: theory and simulation study

    Dagan Feng;Koon-Pong Wong;Chi-Ming Wu;Wan-Chi Siu

  • Deep Convolutional Neural Networks for Human Action Recognition Using Depth Maps and Postures

    Aouaidjia Kamel;Bin Sheng;Po Yang;Ping Li

  • Feature-Based Image Patch Approximation for Lung Tissue Classification

    Yang Song;Weidong Cai;Yun Zhou;D. D. Feng

  • Step-wise integration of deep class-specific learning for dermoscopic image segmentation

    Lei Bi;Jinman Kim;Euijoon Ahn;Ashnil Kumar

  • Automatic Skin Lesion Analysis using Large-scale Dermoscopy Images and Deep Residual Networks

    Lei Bi;Jinman Kim;Euijoon Ahn;Dagan Feng

Frequent Co-Authors

Weidong Cai
Weidong Cai University of Sydney
Yang Song
Yang Song California Institute of Technology
Zheru Chi
Zheru Chi Hong Kong Polytechnic University
Yong Xia
Yong Xia Northwestern Polytechnical University
Ron Kikinis
Ron Kikinis Brigham and Women's Hospital
Wan-Chi Siu
Wan-Chi Siu Hong Kong Polytechnic University
Heng Huang
Heng Huang University of Pittsburgh
Yue Wang
Yue Wang Zhejiang University
Kewei Chen
Kewei Chen Arizona State University
Ke Yan
Ke Yan University of Sydney

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