World's Best Scientists 2026 revealed!

Jar-Ferr Yang 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 Jar-Ferr Yang 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+

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

Jar-Ferr Yang 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 Jar-Ferr Yang 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+

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

Overview

Jar-Ferr Yang is affiliated with National Cheng Kung University in Taiwan, with a primary research focus in the field of Computer Science. Their work emphasizes Computer Vision and Pattern Recognition, covering a broad range of topics related to advanced imaging and video processing.

The main fields of study in which Jar-Ferr Yang has contributed include:

  • Computer Vision and Pattern Recognition
  • Media Technology
  • Automotive Engineering
  • Sociology and Political Science
  • Artificial Intelligence

The scientist's research spans several main topics, particularly within imaging and neural networks, such as:

  • Advanced Vision and Imaging
  • Advanced Image Processing Techniques
  • Image Enhancement Techniques
  • Image Processing Techniques and Applications
  • Advanced Neural Network Applications
  • Video Analysis and Summarization
  • Video Surveillance and Tracking Methods

Jar-Ferr Yang has published research in a variety of technical venues. Frequent publication venues include:

  • 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
  • Research Square (Research Square)
  • EURASIP Journal on Image and Video Processing
  • IET Computer Vision
  • IEEE Systems Journal

Selected recent papers authored or co-authored by Jar-Ferr Yang illustrate the scope of their research interests:

  • "Enhancing Fan Engagement in a 5G Stadium With AI-Based Technologies and Live Streaming", 2022, IEEE Systems Journal
  • "Shape-reserved stereo matching with segment-based cost aggregation and dual-path refinement", 2020, EURASIP Journal on Image and Video Processing
  • "Improved quadruple sparse census transform and adaptive multi-shape aggregation algorithms for precise stereo matching", 2021, IET Computer Vision
  • "Improved vehicle detection systems with double-layer LSTM modules", 2022, EURASIP Journal on Advances in Signal Processing
  • "An image-guided network for depth edge enhancement", 2022, EURASIP Journal on Image and Video Processing

Collaborative efforts form an important part of Jar-Ferr Yang's research activity. Frequent co-authors include:

  • Wei-Jong Yang
  • Kuo-Cheng Tu
  • Yen-Ting Chen
  • Wan-Ju Liow
  • Shao-Fu Chen

Best Publications

  • Source number estimators using transformed Gerschgorin radii

    Hsien-Tsai Wu;Jar-Ferr Yang;Fwu-Kuen Chen

  • Adaptive eigensubspace algorithms for direction or frequency estimation and tracking

    J.-F. Yang;M. Kaveh

  • A Fast Mode Decision Algorithm and Its VLSI Design for H.264/AVC Intra-Prediction

    Jia-Ching Wang;Jhing-Fa Wang;Jar-Ferr Yang;Jang-Ting Chen

  • Combined techniques of singular value decomposition and vector quantization for image coding

    Jar-Ferr Yang;Chiou-Liang Lu

  • Enhanced Intra-4 $,times,$ 4 Mode Decision for H.264/AVC Coders

    Chao-Hsuing Tseng;Hung-Ming Wang;Jar-Ferr Yang

  • Efficient rate-distortion estimation for H.264/AVC coders

    Yu-Kuang Tu;Jar-Ferr Yang;Ming-Ting Sun

  • Fast variable-size block motion estimation using merging procedure with an adaptive threshold

    Yu-Kuang Tu;Jar-Ferr Yang;Yi-Nung Shen;Ming-Ting Sun

  • Source number estimator using Gerschgorin disks

    Hsien-Tsai Wu;Jar-Ferr Yang;Fwu-Kuen Chen

  • Computation reduction for motion search in low rate video coders

    Jar-Ferr Yang;Shih-Cheng Chang;Chin-Yun Chen

  • Effective Subblock-Based and Pixel-Based Fast Direction Detections for H.264 Intra Prediction

    An-Chao Tsai;Jhing-Fa Wang;Jar-Ferr Yang;Wei-Guang Lin

  • Improved Principal Component Regression for Face Recognition Under Illumination Variations

    Shih-Ming Huang;Jar-Ferr Yang

  • Linear Discriminant Regression Classification for Face Recognition

    Shih-Ming Huang;Jar-Ferr Yang

  • Combined 2-D transform and quantization architectures for H.264 video coders

    Heng-Yao Lin;Yi-Chih Chao;Che-Hong Chen;Bin-Da Liu

  • Parallel Reconfigurable Computing-Based Mapping Algorithm for Motion Estimation in Advanced Video Coding

    Anand Paul;Yung-Chuan Jiang;Jhing-Fa Wang;Jar-Ferr Yang

  • Color image segmentation using fuzzy C-means and eigenspace projections

    Jar-Ferr Yang;Shu-Sheng Hao;Pau-Choo Chung

  • Recursive architectures for realizing modified discrete cosine transform and its inverse

    Che-Hong Chen;Bin-Da Liu;Jar-Ferr Yang

  • High throughput 2-D transform architectures for H.264 advanced video coders

    Zhan-Yuan Cheng;Che-Hong Chen;Bin-Da Liu;Jar-Ferr Yang

  • Superimposed Sparse Parameter Classifiers for Face Recognition

    Qingxiang Feng;Chun Yuan;Jeng-Shyang Pan;Jar-Ferr Yang

  • Adaptive group-of-pictures and scene change detection methods based on existing H.264 advanced video coding information

    Jun-Ren Ding;Jar-Ferr Yang

  • IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY Editor-in-Chief

    Chang Wen Chen;Hamid Gharavi;Thomas Sikora;Ishfaq Ahmad

Frequent Co-Authors

Pau-Choo Chung
Pau-Choo Chung National Cheng Kung University
Mostafa Kaveh
Mostafa Kaveh University of Minnesota
Ming-Ting Sun
Ming-Ting Sun University of Washington
Anand Paul
Anand Paul Kyungpook National University
Changsheng Xu
Changsheng Xu Chinese Academy of Sciences
Shipeng Li
Shipeng Li Chinese University of Hong Kong, Shenzhen
M.N.S. Swamy
M.N.S. Swamy Concordia University
Eckehard Steinbach
Eckehard Steinbach Technical University of Munich
Mostafa Fatemi
Mostafa Fatemi Mayo Clinic

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Computer Science in the USA can open multiple pathways for professional growth. For those looking to quickly boost their credentials, there are easy certifications to get that offer a strong return on investment. These certifications can help you specialize and stand out in the tech job market without committing years to study.

If you’re considering further education, quick masters degrees online are an efficient way to deepen your expertise and earn a valuable qualification in a shorter timeframe. This is ideal for working professionals or graduates seeking rapid career advancement.

When choosing a degree, it’s wise to research the most valuable masters degrees linked to industry demand. Fields like artificial intelligence, cybersecurity, and data science often rank highly for both employability and earning potential.

For those just starting out, an associates degree online is a flexible, affordable option. It serves as a stepping stone, providing foundational knowledge and the ability to transfer credits to a bachelor's program later on.

Best Scientists Citing Jar-Ferr Yang

Trending Scientists

Recently Published Articles