World's Best Scientists 2026 revealed!
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Computer Science
Pakistan
2026

D-Index & Metrics

Computer Science

D-Index
65
Citations
12504
World Ranking
2502
National Ranking
2

Research.com Recognitions

  • 2026 - Research.com Computer Science in Pakistan Leader Award
  • 2025 - Research.com Computer Science in Pakistan Leader Award
  • 2023 - Research.com Computer Science in Pakistan Leader Award
  • 2022 - Research.com Computer Science in Pakistan Leader Award

Overview

Muhammad Sharif is affiliated with COMSATS University Islamabad in Pakistan. Their research contributions span the fields of Medicine and Computer Science, with a focus on several interdisciplinary subfields including Oncology, Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, and Pulmonary and Respiratory Medicine.

The main topics of Muhammad Sharif's work encompass:

  • Cutaneous Melanoma Detection and Management
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Gastrointestinal Bleeding Diagnosis and Treatment
  • Image Processing Techniques and Applications
  • Digital Media Forensic Detection
  • Pneumonia and Respiratory Infections

Muhammad Sharif has published in several recognized venues, indicating active involvement in both computer science and medical domains. Frequent publication venues include:

  • Computers & Electrical Engineering
  • Computers, Materials & Continua (Print)
  • PeerJ Computer Science
  • Methods
  • Cognitive Computation

Among their recent published papers are:

  • "Pixels to Classes: Intelligent Learning Framework for Multiclass Skin Lesion Localization and Classification," 2021, Computers & Electrical Engineering
  • "Prediction of COVID-19 - Pneumonia based on Selected Deep Features and One Class Kernel Extreme Learning Machine," 2020, Computers & Electrical Engineering
  • "From ECG signals to images: a transformation based approach for deep learning," 2021, PeerJ Computer Science
  • "A hierarchical three-step superpixels and deep learning framework for skin lesion classification," 2021, Methods
  • "FF-UNet: a U-Shaped Deep Convolutional Neural Network for Multimodal Biomedical Image Segmentation," 2022, Cognitive Computation

Muhammad Sharif collaborates frequently with several researchers, including:

  • Muhammad Attique Khan
  • Tallha Akram
  • Seifedine Kadry
  • Amjad Rehman
  • Jamal Hussain Shah

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 using fusion of hand crafted and deep learning features

    Tanzila Saba;Ahmed Sameh Mohamed;Mohammed Ahmed El-Affendi;Javeria Amin;Javeria Amin

  • Big data analysis for brain tumor detection: Deep convolutional neural networks

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

  • Internet of Things (IoT) Operating Systems Support, Networking Technologies, Applications, and Challenges: A Comparative Review

    Farhana Javed;Muhamamd Khalil Afzal;Muhammad Sharif;Byung-Seo Kim

  • Brain tumor detection using statistical and machine learning method.

    Javaria Amin;Muhammad Sharif;Mudassar Raza;Tanzila Saba

  • 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 Survey on Medical Image Segmentation

    Saleha Masood;Muhammad Sharif;Afifa Masood;Mussarat Yasmin

  • 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 and classification: A framework of marker-based watershed algorithm and multilevel priority features selection.

    Muhammad A. Khan;Ikram U. Lali;Amjad Rehman;Mubashar Ishaq

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

    Javaria Amin;Muhammad Sharif;Mudassar Raza;Tanzila Saba

  • A Survey of Password Attacks and Comparative Analysis on Methods for Secure Authentication

    Mudassar Raza;Muhammad Iqbal;Muhammad Sharif;Waqas Haider

  • 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

  • A method for the detection and classification of diabetic retinopathy using structural predictors of bright lesions

    Javeria Amin;Muhammad Sharif;Mussarat Yasmin;Hussam Ali

  • Brain Tumor Detection by Using Stacked Autoencoders in Deep Learning

    Javaria Amin;Muhammad Sharif;Nadia Gul;Mudassar Raza

Frequent Co-Authors

Mudassar Raza
Mudassar Raza Namal College
Mussarat Yasmin
Mussarat Yasmin University of Gujrat
Muhammad Attique Khan
Muhammad Attique Khan Prince Mohammad bin Fahd University
Tanzila Saba
Tanzila Saba Prince Sultan University
Tallha Akram
Tallha Akram Prince Sattam Bin Abdulaziz University
Steven Lawrence Fernandes
Steven Lawrence Fernandes Karunya University
Amjad Rehman
Amjad Rehman Prince Sultan University
Seifedine Kadry
Seifedine Kadry Lebanese American University
Muhammad Iqbal
Muhammad Iqbal University of Agriculture Faisalabad
Mubashir Husain Rehmani
Mubashir Husain Rehmani Munster Technological University

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