World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
10230
World Ranking
10487
National Ranking
4389

Chengjun Liu 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 Chengjun Liu 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: 143 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Chengjun Liu 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 Chengjun Liu 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Chengjun Liu is affiliated with the New Jersey Institute of Technology in the United States and has contributed extensively to the field of computer science, particularly focusing on computer vision and pattern recognition. Their research integrates areas such as artificial intelligence, radiology imaging, and industrial engineering, reflecting a multidisciplinary approach within the broader domain of advanced neural networks and machine learning applications.

The scientist's work emphasizes diverse topics, including:

  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • Adversarial Robustness in Machine Learning
  • Visual Attention and Saliency Detection
  • Video Analysis and Summarization

The publication record of Chengjun Liu spans several venues, highlighting contributions to both conference proceedings and journals. Frequent publication venues include:

  • arXiv (Cornell University)
  • 2022 IEEE International Conference on Consumer Electronics (ICCE)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE Access
  • IEEE Open Journal of Signal Processing

Recent papers authored or co-authored by Liu showcase a focus on semantic segmentation, attention mechanisms, and adversarial methods in deep learning. Notable papers include:

  • "Deep Guidance Decoder with Semantic Boundary Learning for Boundary-Aware Semantic Segmentation," 2022, 2022 IEEE International Conference on Consumer Electronics (ICCE)
  • "DeepGBASS: Deep Guided Boundary-Aware Semantic Segmentation," 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "GSANet: Semantic Segmentation with Global and Selective Attention," 2020, arXiv (Cornell University)
  • "Multiexpert Adversarial Regularization for Robust and Data-Efficient Deep Supervised Learning," 2022, IEEE Access
  • "1st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation," 2024, arXiv (Cornell University)

Collaboration is a significant aspect of Liu's research, indicated by frequent co-authors such as:

  • Mostafa El-Khamy
  • Kee-Bong Song
  • Hai Su
  • Jungwon Lee
  • Dongwoon Bai

Best Publications

  • Gabor feature based classification using the enhanced fisher linear discriminant model for face recognition

    Chengjun Liu;H. Wechsler

  • Gabor-based kernel PCA with fractional power polynomial models for face recognition

    Chengjun Liu

  • Independent component analysis of Gabor features for face recognition

    Chengjun Liu;H. Wechsler

  • Evolutionary pursuit and its application to face recognition

    C. Liu;H. Wechsler

  • A shape- and texture-based enhanced Fisher classifier for face recognition

    Chengjun Liu;H. Wechsler

  • A Bayesian discriminating features method for face detection

    Chengjun Liu

  • Robust coding schemes for indexing and retrieval from large face databases

    Chengjun Liu;H. Wechsler

  • Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance

    Chengjun Liu

  • Comparative Assessment of Independent Component Analysis (ICA) for Face Recognition

    Chengjun Liu;Harry Wechsler

  • Enhanced Fisher linear discriminant models for face recognition

    Chengjun Liu;H. Wechsler

  • A Gabor feature classifier for face recognition

    Chengjun Liu;H. Wechsler

  • Comparative assessment of content-based face image retrieval in different color spaces

    Peichung Shih;Chengjun Liu

  • Color space normalization: Enhancing the discriminating power of color spaces for face recognition

    Jian Yang;Chengjun Liu;Lei Zhang

  • Color Image Discriminant Models and Algorithms for Face Recognition

    Jian Yang;Chengjun Liu

  • Learning the Uncorrelated, Independent, and Discriminating Color Spaces for Face Recognition

    Chengjun Liu

  • Fusion of color, local spatial and global frequency information for face recognition

    Zhiming Liu;Chengjun Liu

  • Face detection using discriminating feature analysis and Support Vector Machine

    Peichung Shih;Chengjun Liu

  • A Hybrid Color and Frequency Features Method for Face Recognition

    Zhiming Liu;Chengjun Liu

  • Enhanced independent component analysis and its application to content based face image retrieval

    Chengjun Liu

  • Smart Traffic Monitoring System Using Computer Vision and Edge Computing

    Guanxiong Liu;Hang Shi;Abbas Kiani;Abdallah Khreishah

  • ICA Color Space for Pattern Recognition

    Chengjun Liu;Jian Yang

Frequent Co-Authors

Harry Wechsler
Harry Wechsler George Mason University
Jian Yang
Jian Yang University of Birmingham
Jingyu Yang
Jingyu Yang Nanjing University of Science and Technology
Nirwan Ansari
Nirwan Ansari New Jersey Institute of Technology
Srinivas Gutta
Srinivas Gutta Philips (Netherlands)
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Abdallah Khreishah
Abdallah Khreishah New Jersey Institute of Technology

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