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Helmi Zulhaidi Mohd Shafri

Helmi Zulhaidi Mohd Shafri

D-Index & Metrics

Computer Science

D-Index
42
Citations
5801
World Ranking
8517
National Ranking
17

Helmi Zulhaidi Mohd Shafri 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 Helmi Zulhaidi Mohd Shafri 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: 197 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Helmi Zulhaidi Mohd Shafri 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 Helmi Zulhaidi Mohd Shafri 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Helmi Zulhaidi Mohd Shafri is affiliated with Universiti Putra Malaysia in Malaysia. The research work primarily spans Environmental Science and Engineering, with significant contributions in the following subfields:

  • Ecology
  • Environmental Engineering
  • Global and Planetary Change
  • Media Technology
  • Plant Science

The main topics addressed in the research include:

  • Remote Sensing and LiDAR Applications
  • Remote-Sensing Image Classification
  • Remote Sensing in Agriculture
  • Land Use and Ecosystem Services
  • Oil Palm Production and Sustainability
  • Flood Risk Assessment and Management
  • Remote Sensing and Land Use

Helmi Zulhaidi Mohd Shafri has contributed to numerous publications, including recent papers such as:

  • "Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms" (2020) published in Remote Sensing Applications Society and Environment
  • "Deep Convolutional Neural Network for Large-Scale Date Palm Tree Mapping from UAV-Based Images" (2021) published in Remote Sensing
  • "A Deep Learning Approach for Dengue Fever Prediction in Malaysia Using LSTM with Spatial Attention" (2023) published in International Journal of Environmental Research and Public Health
  • "Remotely-Sensed Ecosystem Health Assessment (RSEHA) model for assessing the changes of ecosystem health of Lake Urmia Basin" (2021) published in International Journal of Image and Data Fusion
  • "Improving Forest Above-Ground Biomass Estimation by Integrating Individual Machine Learning Models" (2024) published in Forests

The frequent co-authors collaborating with Helmi Zulhaidi Mohd Shafri include:

  • Aimrun Wayayok
  • Shaiful Jahari Hashim
  • Ahmad Fikri Abdullah
  • Yuhao Ang
  • Nur Shafira Nisa Shaharum

The research outputs are often disseminated in multiple publication venues, predominantly in:

  • IOP Conference Series Earth and Environmental Science
  • Remote Sensing
  • ISPRS International Journal of Geo-Information
  • Geocarto International
  • Remote Sensing Applications Society and Environment

Overall, the research profile underscores a focus on applying remote sensing and machine learning techniques across various environmental and agricultural domains, emphasizing ecosystem monitoring, mapping, and predictive modeling relevant to Malaysia and broader regional contexts.

Best Publications

  • The Performance of Maximum Likelihood, Spectral Angle Mapper, Neural Network and Decision Tree Classifiers in Hyperspectral Image Analysis

    Helmi Zulhaidi Mohd Shafri;Affendi Suhaili;Shattri Mansor

  • Lineament mapping and its application in landslide hazard assessment: a review

    Mohammad Firuz Ramli;N. Yusof;Mohd Kamil Yusoff;Hafizan Juahir

  • Hyperspectral imagery for mapping disease infection in oil palm plantation using vegetation indices and red edge techniques.

    Helmi Zulhaidi Mohd Shafri;Nasrulhapiza Hamdan

  • A review on hyperspectral remote sensing for homogeneous and heterogeneous forest biodiversity assessment

    Azadeh Ghiyamat;Helmi Z. M. Shafri

  • Young and mature oil palm tree detection and counting using convolutional neural network deep learning method

    Nurulain Abd Mubin;Eiswary Nadarajoo;Helmi Zulhaidi Mohd Shafri;Alireza Hamedianfar

  • Oil palm fruit bunch grading system using red, green and blue digital number.

    Meftah Salem M. Alfatni;Abdul Rashid Mohamed Shariff;Helmi Zulhaidi Mohd Shafri;Osama M. Ben Saaed

  • Image Classification in Remote Sensing

    Jwan Al-doski;Shattri B. Mansor;Helmi Zulhaidi Mohd Shafri

  • Data Fusion Technique Using Wavelet Transform and Taguchi Methods for Automatic Landslide Detection From Airborne Laser Scanning Data and QuickBird Satellite Imagery

    Biswajeet Pradhan;Mustafa Neamah Jebur;Helmi Zulhaidi Mohd Shafri;Mahyat Shafapour Tehrany

  • Early detection of basal stem rot disease Ganoderma in oil palms based on hyperspectral reflectance data using pattern recognition algorithms

    Shohreh Liaghat;Reza Ehsani;Shattri Mansor;Helmi Z. M. Shafri

  • Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas city, Iran

    Mohsen Dadras;Mohsen Dadras;Helmi Z.M. Shafri;Noordin Ahmad;Biswajeet Pradhan

  • Classification of oil palm fresh fruit bunches based on their maturity using portable four-band sensor system

    Osama Mohammed Ben Saeed;Sindhuja Sankaran;Abdul Rashid Mohamed Shariff;Helmi Zulhaidi Mohd Shafri

  • Spectral discrimination of healthy and Ganoderma-infected oil palms from hyperspectral data

    Helmi Z. M. Shafri;Mohd I. Anuar;Idris A. Seman;Nisfariza M. Noor

  • An analysis of LULC change detection using remotely sensed data; A Case study of Bauchi City

    Unknown

  • Hyperspectral Remote Sensing of Vegetation Using Red Edge Position Techniques

    Helmi Zulhaidi Mohd Shafri;Mohamad Amran Mohd Salleh;Azadeh Ghiyamat

  • NDVI Differencing and Post-classification to Detect Vegetation Changes in Halabja City, Iraq.

    Shattri Mansor;Helmi Zulhaidi Mohd Shafri;Jwan Al-doski

  • Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data

    Mustafa Ridha Mezaal;Biswajeet Pradhan;Maher Ibrahim Sameen;Helmi Zulhaidi Mohd Shafri

  • Semi-automatic detection and counting of oil palm trees from high spatial resolution airborne imagery

    Helmi Z. M. Shafri;Nasrulhapiza Hamdan;M. Iqbal Saripan

  • Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember

    Azadeh Ghiyamat;Helmi Zulhaidi Mohd Shafri;Ghafour Amouzad Mahdiraji;Abdul Rashid Mohamed Shariff

  • Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery

    Mustafa Neamah Jebur;Helmi Zulhaidi Mohd Shafri;Biswajeet Pradhan;Mahyat Shafapour Tehrany

  • Drone-based land-cover mapping using a fuzzy unordered rule induction algorithm integrated into object-based image analysis

    Bahareh Kalantar;Shattri Bin Mansor;Maher Ibrahim Sameen;Biswajeet Pradhan

  • Improving detailed rule-based feature extraction of urban areas from WorldView-2 image and lidar data

    Alireza Hamedianfar;Helmi Zulhaidi Mohd Shafri;Shattri Mansor;Noordin Ahmad

Frequent Co-Authors

Biswajeet Pradhan
Biswajeet Pradhan University of Technology Sydney
Hafizan Juahir
Hafizan Juahir Sultan Zainal Abidin University
Sariah Meon
Sariah Meon Universiti Putra Malaysia
Alex M. Lechner
Alex M. Lechner Monash University
Jocelyn Chanussot
Jocelyn Chanussot Grenoble Alpes University
Badrul Azhar
Badrul Azhar Universiti Putra Malaysia

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