World's Best Scientists 2026 revealed!
Hassan Ghassemian

Hassan Ghassemian

D-Index & Metrics

Computer Science

D-Index
38
Citations
6933
World Ranking
10150
National Ranking
15

Hassan Ghassemian 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 Hassan Ghassemian 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: 298 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Hassan Ghassemian 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 Hassan Ghassemian 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Hassan Ghassemian is affiliated with Tarbiat Modares University in Iran, focusing primarily on research within engineering and computer science. Their scholarly work is concentrated on media technology, aerospace engineering, atmospheric science, computer vision and pattern recognition, and artificial intelligence.

Their main topics of study include remote-sensing image classification, advanced image fusion techniques, remote sensing and land use, infrared target detection methodologies, advanced chemical sensor technologies, image and signal denoising methods, and domain adaptation and few-shot learning.

Ghassemian has a substantial record of publications in several prominent venues, with frequent appearances in the International Journal of Remote Sensing, the arXiv repository by Cornell University, The Egyptian Journal of Remote Sensing and Space Science, IEEE Geoscience and Remote Sensing Letters, and Zenodo from CERN. Their recent papers exemplify their research interests and include:

  • An overview on spectral and spatial information fusion for hyperspectral image classification: Current trends and challenges (2020), published in Information Fusion
  • Hyperspectral Unmixing Using Deep Convolutional Autoencoders in a Supervised Scenario (2020), published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Hyperspectral image classification by optimizing convolutional neural networks based on information theory and 3D-Gabor filters (2021), published in International Journal of Remote Sensing
  • Clustering based background learning for hyperspectral anomaly detection (2023), published in The Egyptian Journal of Remote Sensing and Space Science
  • Second-Order Total Generalized Variation Regularization for Pansharpening (2020), published in IEEE Geoscience and Remote Sensing Letters

Their collaborative network includes repeated co-authorship with researchers such as Maryam Imani, Mohamad Ebrahim Aghili, Arash Saboori, Shiva Maleki, and Farshid Khajehrayeni. These collaborations span multiple publications, contributing to a diversified scholarly output.

Best Publications

  • A review of remote sensing image fusion methods

    Hassan Ghassemian

  • MRI and PET image fusion by combining IHS and retina-inspired models

    Sabalan Daneshvar;Hassan Ghassemian

  • An overview on spectral and spatial information fusion for hyperspectral image classification: Current trends and challenges

    Maryam Imani;Hassan Ghassemian

  • Combining the spectral PCA and spatial PCA fusion methods by an optimal filter

    Hamid Reza Shahdoosti;Hassan Ghassemian

  • Reflectance Vis/NIR spectroscopy for nondestructive taste characterization of Valencia oranges

    Bahareh Jamshidi;Saeid Minaei;Ezzedin Mohajerani;Hassan Ghassemian

  • Spectral Unmixing of Hyperspectral Imagery Using Multilayer NMF

    Roozbeh Rajabi;Hassan Ghassemian

  • Spectral–Spatial Classification of Hyperspectral Data Using Local and Global Probabilities for Mixed Pixel Characterization

    Mahdi Khodadadzadeh;Jun Li;Antonio Plaza;Hassan Ghassemian

  • Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal

    Maryam Mohebbi;Hassan Ghassemian

  • Nonlinear IHS: A Promising Method for Pan-Sharpening

    Morteza Ghahremani;Hassan Ghassemian

  • Improving hyperspectral image classification by combining spectral, texture, and shape features

    Fardin Mirzapour;Hassan Ghassemian

  • Applied machine vision and artificial neural network for modeling and controlling of the grape drying process

    Nasser Behroozi Khazaei;Teymour Tavakoli;Hassan Ghassemian;Mohammad Hadi Khoshtaghaza

  • Classification of heart sound signal using curve fitting and fractal dimension

    Maryam Hamidi;Hassan Ghassemian;Maryam Imani

  • Content-based medical image classification using a new hierarchical merging scheme

    Hossein Pourghassem;Hassan Ghassemian

  • Remote Sensing Image Fusion Using Ripplet Transform and Compressed Sensing

    Morteza Ghahremani;Hassan Ghassemian

  • Fusion of MS and PAN Images Preserving Spectral Quality

    Hamid Reza Shahdoosti;Hassan Ghassemian

  • A Compressed-Sensing-Based Pan-Sharpening Method for Spectral Distortion Reduction

    Morteza Ghahremani;Hassan Ghassemian

  • Band Clustering-Based Feature Extraction for Classification of Hyperspectral Images Using Limited Training Samples

    Maryam Imani;Hassan Ghassemian

  • Integrating Hierarchical Segmentation Maps With MRF Prior for Classification of Hyperspectral Images in a Bayesian Framework

    Meysam Golipour;Hassan Ghassemian;Fardin Mirzapour

  • Feature space discriminant analysis for hyperspectral data feature reduction

    Maryam Imani;Hassan Ghassemian

  • Feature Extraction Using Weighted Training Samples

    Maryam Imani;Hassan Ghassemian

Frequent Co-Authors

David A. Landgrebe
David A. Landgrebe Purdue University West Lafayette
Saeid Minaei
Saeid Minaei Tarbiat Modares University
Hamid Dehghani
Hamid Dehghani University of Birmingham
Antonio Plaza
Antonio Plaza University of Extremadura
Jose M. Bioucas-Dias
Jose M. Bioucas-Dias Instituto Superior Técnico
Xia Li
Xia Li East China Normal University

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