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Muhammad Sharif

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 56 2887 2762 24 24 130 9880

Muhammad Sharif publications per year

The chart shows the history of publications by Muhammad Sharif between 1976 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Muhammad Sharif published across 50 years, from 1976 to 2025, averaging 3.2 papers a year. Output peaked at 26 publications in 2021. 17 of the 158 publications appeared in the last two years.

No. of publications
5 10 15 20 25
Bar chart. Horizontal axis: year, 1976 to 2025. Vertical axis: number of publications, 0 to 26. Peak 26 publications in 2021. 1976: 1 publication 1977: 0 publications 1978: 0 publications 1979: 0 publications 1980: 0 publications 1981: 0 publications 1982: 0 publications 1983: 0 publications 1984: 0 publications 1985: 0 publications 1986: 0 publications 1987: 0 publications 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 0 publications 1993: 0 publications 1994: 0 publications 1995: 0 publications 1996: 0 publications 1997: 0 publications 1998: 0 publications 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 0 publications 2005: 0 publications 2006: 0 publications 2007: 0 publications 2008: 0 publications 2009: 1 publication 2010: 1 publication 2011: 1 publication 2012: 1 publication 2013: 3 publications 2014: 5 publications 2015: 5 publications 2016: 3 publications 2017: 8 publications 2018: 16 publications 2019: 13 publications 2020: 25 publications 2021: 26 publications 2022: 21 publications 2023: 11 publications 2024: 11 publications 2025: 6 publications
1976 2025

158 publications in total across all disciplines

View publications per year as a table
Muhammad Sharif: publications per year, 1976 to 2025
Year Publications
1976 1
1977 0
1978 0
1979 0
1980 0
1981 0
1982 0
1983 0
1984 0
1985 0
1986 0
1987 0
1988 0
1989 0
1990 0
1991 0
1992 0
1993 0
1994 0
1995 0
1996 0
1997 0
1998 0
1999 0
2000 0
2001 0
2002 0
2003 0
2004 0
2005 0
2006 0
2007 0
2008 0
2009 1
2010 1
2011 1
2012 1
2013 3
2014 5
2015 5
2016 3
2017 8
2018 16
2019 13
2020 25
2021 26
2022 21
2023 11
2024 11
2025 6
Total 158
Download as CSV

Muhammad Sharif publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Muhammad Sharif sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 128–137 publications, is where this scientist sits. 38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38–47 publications 804+

This scientist: 130 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386 130
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
Download as CSV

Muhammad Sharif D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Muhammad Sharif sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 56 D-Index, is where this scientist sits. 30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170 56
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Overview

Muhammad Sharif is affiliated with King Fahd University of Petroleum and Minerals in Saudi Arabia. Sharif's research output spans multiple interdisciplinary fields combining computer science and medicine, with a focus on artificial intelligence applications in imaging and diagnostics.

The scientist's main research areas include:

  • Computer Science
  • Medicine

Within these broader categories, Sharif's work frequently addresses subfields such as:

  • Computer Vision and Pattern Recognition
  • Plant Science
  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Neurology

The research topics covered highlight a concentration on applied AI techniques in medical and agricultural contexts, including:

  • Smart Agriculture and AI
  • Digital Imaging for Blood Diseases
  • Anomaly Detection Techniques and Applications
  • COVID-19 diagnosis using AI
  • Brain Tumor Detection and Classification
  • Spectroscopy and Chemometric Analyses
  • AI in cancer detection

Sharif has published research in several notable scientific venues, frequently contributing to:

  • IEEE Access
  • Computers, Materials & Continua
  • Multimedia Tools and Applications
  • Sensors
  • Neural Computing and Applications

Examples of recent published papers include:

  • "Brain tumor detection and classification using machine learning: a comprehensive survey" (2021) in Complex & Intelligent Systems
  • "Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization" (2021) in Diagnostics
  • "Attributes based skin lesion detection and recognition: A mask RCNN and transfer learning-based deep learning framework" (2021) in Pattern Recognition Letters
  • "Multi-Class Skin Lesion Detection and Classification via Teledermatology" (2021) in IEEE Journal of Biomedical and Health Informatics
  • "A framework of human action recognition using length control features fusion and weighted entropy-variances based feature selection" (2020) in Image and Vision Computing

Collaborative work involves frequent co-authors who appear repeatedly in Sharif's publications. These co-authors include:

  • Muhammad Attique Khan
  • Seifedine Kadry
  • Javeria Amin
  • Muhammad Almas Anjum
  • Mussarat Yasmin

The distribution of publications and collaborations points to a multidisciplinary approach, integrating domain knowledge in AI-driven medical diagnostics and agriculture-related computer vision techniques.

Best Publications

  • A distinctive approach in brain tumor detection and classification using MRI

    Javeria Amin;Muhammad Sharif;Mussarat Yasmin;Steven Lawrence Fernandes

  • An automated detection and classification of citrus plant diseases using image processing techniques: A review

    Zahid Iqbal;Muhammad Attique Khan;Muhammad Attique Khan;Muhammad Sharif;Jamal Hussain Shah

  • Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection

    Muhammad Sharif;Muhammad Attique Khan;Muhammad Attique Khan;Zahid Iqbal;Muhammad Faisal Azam

  • Brain tumor detection and classification using machine learning: a comprehensive survey

    Javaria Amin;Javaria Amin;Muhammad Sharif;Anandakumar Haldorai;Mussarat Yasmin

  • Brain tumor detection using statistical and machine learning method.

    Javaria Amin;Muhammad Sharif;Mudassar Raza;Tanzila Saba

  • A citrus fruits and leaves dataset for detection and classification of citrus diseases through machine learning.

    Hafiz Tayyab Rauf;Basharat Ali Saleem;M. Ikram Ullah Lali;Muhammad Attique Khan

  • A decision support system for multimodal brain tumor classification using deep learning

    Muhammad Imran Sharif;Muhammad Attique Khan;Musaed Alhussein;Khursheed Aurangzeb

  • Skin lesion segmentation and multiclass classification using deep learning features and improved moth flame optimization

    Muhammad Attique Khan;Muhammad Sharif;Tallha Akram;Robertas Damaševičius

  • Symptom based automated detection of citrus diseases using color histogram and textural descriptors

    H. Ali;M.I. Lali;M.Z. Nawaz;M. Sharif

  • CCDF: Automatic system for segmentation and recognition of fruit crops diseases based on correlation coefficient and deep CNN features

    Muhammad Attique Khan;Tallha Akram;Muhammad Sharif;Muhammad Awais

  • Attributes based skin lesion detection and recognition: A mask RCNN and transfer learning-based deep learning framework

    Muhammad Attique Khan;Tallha Akram;Yu-Dong Zhang;Muhammad Sharif

  • Brain tumor classification based on DWT fusion of MRI sequences using convolutional neural network

    Javaria Amin;Muhammad Sharif;Nadia Gul;Mussarat Yasmin

  • An Optimized Method for Segmentation and Classification of Apple Diseases Based on Strong Correlation and Genetic Algorithm Based Feature Selection

    Muhammad Attique Khan;M Ikram Ullah Lali;Muhammad Sharif;Kashif Javed

  • A framework for offline signature verification system: Best features selection approach

    Muhammad Sharif;Muhammad Attique Khan;Muhammad Faisal;Mussarat Yasmin

  • An integrated design of particle swarm optimization (PSO) with fusion of features for detection of brain tumor

    Muhammad Sharif;Javaria Amin;Mudassar Raza;Mussarat Yasmin

  • Brain tumor detection: a long short-term memory (LSTM)-based learning model

    Javaria Amin;Muhammad Sharif;Mudassar Raza;Tanzila Saba

  • An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

    Muhammad Nasir;Muhammad Attique Khan;Muhammad Sharif;Ikram Ullah Lali

  • Detection of Brain Tumor based on Features Fusion and Machine Learning

    Javeria Amin;Muhammad Sharif;Mudassar Raza;Mussarat Yasmin

  • Multi-Model Deep Neural Network based Features Extraction and Optimal Selection Approach for Skin Lesion Classification

    Muhammad Attique Khan;Muhammad Younus Javed;Muhammad Sharif;Tanzila Saba

  • Brain tumor segmentation and classification by improved binomial thresholding and multi-features selection

    Muhammad Sharif;Uroosha Tanvir;Ehsan Ullah Munir;Muhammad Attique Khan

  • Multi-Class Skin Lesion Detection and Classification via Teledermatology

    Muhammad Attique Khan;Khan Muhammad;Muhammad Sharif;Tallha Akram

  • Hand-crafted and deep convolutional neural network features fusion and selection strategy: An application to intelligent human action recognition

    Muhammad Attique Khan;Muhammad Attique Khan;Muhammad Sharif;Tallha Akram;Mudassar Raza

  • Developed Newton-Raphson based deep features selection framework for skin lesion recognition

    Muhammad Attique Khan;Muhammad Sharif;Tallha Akram;Syed Ahmad Chan Bukhari

  • Skin lesion segmentation and classification: A unified framework of deep neural network features fusion and selection

    Muhammad Attique Khan;Muhammad Imran Sharif;Mudassar Raza;Almas Anjum

  • A framework of human action recognition using length control features fusion and weighted entropy-variances based feature selection

    Farhat Afza;Muhammad Attique Khan;Muhammad Sharif;Seifedine Nimer Kadry

  • From ECG signals to images: a transformation based approach for deep learning.

    Mahwish Naz;Jamal Hussain Shah;Muhammad Attique Khan;Muhammad Sharif

  • Object detection and classification: a joint selection and fusion strategy of deep convolutional neural network and SIFT point features

    Muhammad Rashid;Muhammad Attique Khan;Muhammad Sharif;Mudassar Raza

  • Intelligent fusion-assisted skin lesion localization and classification for smart healthcare

    Muhammad Attique Khan;Khan Muhammad;Muhammad Sharif;Tallha Akram

  • A two-stream deep neural network-based intelligent system for complex skin cancer types classification

    Muhammad Attique Khan;Muhammad Sharif;Tallha Akram;Seifedine Kadry

  • An implementation of optimized framework for action classification using multilayers neural network on selected fused features

    Muhammad Attique Khan;Muhammad Attique Khan;Tallha Akram;Muhammad Sharif;Muhammad Younus Javed

  • An automated system for cucumber leaf diseased spot detection and classification using improved saliency method and deep features selection

    Muhammad Attique Khan;Muhammad Attique Khan;Tallha Akram;Muhammad Sharif;Kashif Javed

  • Appearance based pedestrians’ gender recognition by employing stacked auto encoders in deep learning

    Mudassar Raza;Muhammad Sharif;Mussarat Yasmin;Muhammad Attique Khan

  • Quantum Machine Learning Architecture for COVID-19 Classification Based on Synthetic Data Generation Using Conditional Adversarial Neural Network.

    Javaria Amin;Muhammad Sharif;Nadia Gul;Seifedine Kadry

  • Deep neural network features fusion and selection based on PLS regression with an application for crops diseases classification

    Farah Saeed;Muhammad Attique Khan;Muhammad Sharif;Mamta Mittal

  • Convolutional neural network with batch normalization for glioma and stroke lesion detection using MRI

    Javaria Amin;Javaria Amin;Muhammad Sharif;Muhammad Almas Anjum;Mudassar Raza

  • A deep neural network and classical features based scheme for objects recognition: an application for machine inspection

    Nazar Hussain;Muhammad Attique Khan;Muhammad Sharif;Sajid Ali Khan

Frequent Co-Authors

Xiao-Feng Wu
Xiao-Feng Wu Dalian Institute of Chemical Physics
Muhammad Attique Khan
Muhammad Attique Khan Prince Mohammad bin Fahd University
Tanzila Saba
Tanzila Saba Prince Sultan University
Mussarat Yasmin
Mussarat Yasmin University of Gujrat
Mudassar Raza
Mudassar Raza Namal College
Matthias Beller
Matthias Beller Leibniz Institute for Catalysis
Anke Spannenberg
Anke Spannenberg Leibniz Institute for Catalysis
Amjad Rehman
Amjad Rehman Prince Sultan University
Alexander Villinger
Alexander Villinger University of Rostock
Tallha Akram
Tallha Akram Prince Sattam Bin Abdulaziz University

External Links

Personal website of Muhammad Sharif

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Best Scientists Citing Muhammad Sharif

Xiao-Feng Wu

Xiao-Feng Wu

Dalian Institute of Chemical Physics

Publications: 61

Muhammad Attique Khan

Muhammad Attique Khan

Prince Mohammad bin Fahd University

Publications: 58

Tanzila Saba

Tanzila Saba

Prince Sultan University

Publications: 36

Amjad Rehman

Amjad Rehman

Prince Sultan University

Publications: 29

Muhammad Sharif

Muhammad Sharif

COMSATS University Islamabad

Publications: 26

Tallha Akram

Tallha Akram

Prince Sattam Bin Abdulaziz University

Publications: 14

Seifedine Kadry

Seifedine Kadry

Lebanese American University

Publications: 14

Georgiy B. Shul'pin

Georgiy B. Shul'pin

Plekhanov Russian University of Economics

Publications: 13

Mussarat Yasmin

Mussarat Yasmin

University of Gujrat

Publications: 12

Robertas Damaševičius

Robertas Damaševičius

Kaunas University of Technology

Publications: 12

Yudong Zhang

Yudong Zhang

University of Leicester

Publications: 11

Frédéric Lamaty

Frédéric Lamaty

University of Montpellier

Publications: 9

Mudassar Raza

Mudassar Raza

Namal College

Publications: 9

Shuihua Wang

Shuihua Wang

Xi’an Jiaotong-Liverpool University

Publications: 8

Venkatesan Rajinikanth

Venkatesan Rajinikanth

Saveetha University

Publications: 6

Yunyoung Nam

Yunyoung Nam

Soonchunhyang University

Publications: 6

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2027 Online Graphic Design Bachelor's Degree Programs With No SAT or ACT Requirements
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2027 Best Online Creative Writing Degrees for Jobs
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2027 How to Become an Aquatic Biologist: Salary & Career Paths