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D-Index & Metrics

Computer Science

D-Index
66
Citations
17502
World Ranking
2325
National Ranking
1160

Rogerio Feris 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 Rogerio Feris 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: 285 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Rogerio Feris 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 Rogerio Feris 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: 66 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Overview

Rogerio Feris is a researcher affiliated with IBM in the United States, specializing in computer science with a focus on computer vision and artificial intelligence. Their body of work spans multiple subfields including signal processing, radiology and imaging, and cancer research.

Their recent publications reflect a strong engagement with advanced machine learning techniques and visual recognition. Notable papers include:

  • Targeted Supervised Contrastive Learning for Long-Tailed Recognition, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Baby Steps Towards Few-Shot Learning with Multiple Semantics, 2022, Pattern Recognition Letters
  • A Broad Study on the Transferability of Visual Representations with Contrastive Learning, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IA-RED²: Interpretability-Aware Redundancy Reduction for Vision Transformers, 2021, arXiv (Cornell University)
  • Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Their work integrates topics such as multimodal machine learning applications, domain adaptation and few-shot learning, human pose and action recognition, advanced neural network applications, image and video retrieval techniques, topic modeling, and music and audio processing.

Frequent co-authors collaborating with Rogerio Feris include Leonid Karlinsky, Rameswar Panda, Kate Saenko, Hilde Kuehne, and Aude Oliva.

Research dissemination primarily occurs through venues including arXiv (Cornell University), the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), the IEEE/CVF International Conference on Computer Vision (ICCV), Pattern Recognition Letters, and Lecture Notes in Computer Science.

Best Publications

  • A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

    Zhaowei Cai;Quanfu Fan;Rogério Schmidt Feris;Nuno Vasconcelos

  • BlockDrop: Dynamic Inference Paths in Residual Networks

    Zuxuan Wu;Tushar Nagarajan;Abhishek Kumar;Steven Rennie

  • Cross-Domain Image Retrieval with a Dual Attribute-Aware Ranking Network

    Junshi Huang;Rogerio Feris;Qiang Chen;Shuicheng Yan

  • SpotTune: Transfer Learning Through Adaptive Fine-Tuning

    Yunhui Guo;Honghui Shi;Abhishek Kumar;Kristen Grauman

  • Image ranking and retrieval based on multi-attribute queries

    Behjat Siddiquie;Rogerio S. Feris;Larry S. Davis

  • Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification

    Yongxi Lu;Abhishek Kumar;Shuangfei Zhai;Yu Cheng

  • RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection

    Leonid Karlinsky;Joseph Shtok;Sivan Harary;Eli Schwartz

  • Non-photorealistic camera: depth edge detection and stylized rendering using multi-flash imaging

    Ramesh Raskar;Kar-Han Tan;Rogerio Feris;Jingyi Yu

  • Manifold based analysis of facial expression

    Ya Chang;Changbo Hu;Rogerio Feris;Matthew Turk

  • An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections

    Yu Cheng;Yu Cheng;Felix X. Yu;Rogerio S. Feris;Sanjiv Kumar

  • Deep domain adaptation for describing people based on fine-grained clothing attributes

    Qiang Chen;Junshi Huang;Rogerio Feris;Lisa M Brown

  • Learning to Separate Object Sounds by Watching Unlabeled Video

    Ruohan Gao;Rogério Schmidt Feris;Kristen Grauman

  • A Broader Study of Cross-Domain Few-Shot Learning

    Yunhui Guo;Noel C. Codella;Leonid Karlinsky;James V. Codella

  • Targeted Supervised Contrastive Learning for Long-Tailed Recognition

    Unknown

  • Revisiting RCNN: On Awakening the Classification Power of Faster RCNN

    Bowen Cheng;Yunchao Wei;Honghui Shi;Rogério Schmidt Feris

  • Attribute-based people search in surveillance environments

    Daniel A. Vaquero;Rogerio S. Feris;Duan Tran;Lisa Brown

  • Robust Detection of Abandoned and Removed Objects in Complex Surveillance Videos

    YingLi Tian;R. S. Feris;Haowei Liu;A. Hampapur

  • Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

    Zhonghao Wang;Mo Yu;Yunchao Wei;Rogerio Feris

  • Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation

    Xi Peng;Zhiqiang Tang;Fei Yang;Rogerio S. Feris

  • Designing Category-Level Attributes for Discriminative Visual Recognition

    Felix X. Yu;Liangliang Cao;Rogerio S. Feris;John R. Smith

  • Delta-encoder: an effective sample synthesis method for few-shot object recognition

    Eli Schwartz;Leonid Karlinsky;Joseph Shtok;Sivan Harary

Frequent Co-Authors

Lisa M. Brown
Lisa M. Brown Albert Einstein College of Medicine
Matthew Turk
Matthew Turk Toyota Technological Institute at Chicago
Arun Hampapur
Arun Hampapur Bloom Value
Yu Cheng
Yu Cheng Microsoft (United States)
Yingli Tian
Yingli Tian City University of New York
Ming-Ting Sun
Ming-Ting Sun University of Washington
Sharath Pankanti
Sharath Pankanti IBM (United States)
John R. Smith
John R. Smith IBM (United States)
Raja Giryes
Raja Giryes Tel Aviv University

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