World's Best Scientists 2026 revealed!
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Computer Science
Saudi Arabia
2026

D-Index & Metrics

Computer Science

D-Index
73
Citations
15623
World Ranking
1623
National Ranking
9

Research.com Recognitions

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

Overview

Amjad Rehman is affiliated with Prince Sultan University in Saudi Arabia and has contributed extensively to the field of computer science, with a particular focus on applications in medical imaging and IoT technologies.

Their research spans several subfields, including computer vision and pattern recognition, artificial intelligence, computer networks and communications, radiology, nuclear medicine and imaging, as well as information systems. Central topics in their work include AI in cancer detection, IoT and edge/fog computing, COVID-19 diagnosis using AI, brain tumor detection and classification, radiomics and machine learning in medical imaging, advanced neural network applications, and digital imaging for blood diseases.

Amjad Rehman has authored numerous papers, among which recent notable publications include:

  • "Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists," 2020, Diagnostics
  • "Anomaly-based intrusion detection system for IoT networks through deep learning model," 2022, Computers & Electrical Engineering
  • "Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture," 2020, Microscopy Research and Technique
  • "A Revisit of Internet of Things Technologies for Monitoring and Control Strategies in Smart Agriculture," 2022, Agronomy
  • "Skin cancer detection from dermoscopic images using deep learning and fuzzy k-means clustering," 2021, Microscopy Research and Technique

Their collaborations include frequent co-authors such as Tanzila Saba, Saeed Ali Bahaj, Khalid Haseeb, Faten S. Alamri, and Tariq Mahmood.

Amjad Rehman publishes regularly in several venues, with the most frequent being IEEE Access, Microscopy Research and Technique, Computers, Materials & Continua, IT Professional, and Sensors.

Best Publications

  • Anomaly-based intrusion detection system for IoT networks through deep learning model

    Unknown

  • A Deep Learning Approach for Automated Diagnosis and Multi-Class Classification of Alzheimer’s Disease Stages Using Resting-State fMRI and Residual Neural Networks

    Farheen Ramzan;Muhammad Usman Ghani Khan;Asim Rehmat;Sajid Iqbal;Sajid Iqbal

  • Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists.

    Muhammad Attique Khan;Imran Ashraf;Majed Alhaisoni;Robertas Damaševičius;Robertas Damaševičius

  • Medical Image Segmentation Methods, Algorithms, and Applications

    Alireza Norouzi;Mohd Shafry Mohd Rahim;Ayman Altameem;Tanzila Saba

  • Classification of acute lymphoblastic leukemia using deep learning

    Amjad Rehman;Naveed Abbas;Tanzila Saba;Syed Ijaz ur Rahman

  • Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture

    Amjad Rehman;Muhammad Attique Khan;Tanzila Saba;Zahid Mehmood

  • Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN)

    Sajid Iqbal;M. Usman Ghani;Tanzila Saba;Amjad Rehman

  • Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction

    Tanzila Saba;Muhammad Attique Khan;Amjad Rehman;Souad Larabi Marie-Sainte

  • Skin cancer detection from dermoscopic images using deep learning and fuzzy k-means clustering

    Marriam Nawaz;Zahid Mehmood;Tahira Nazir;Rizwan Ali Naqvi

  • Brain tumor detection and multi-classification using advanced deep learning techniques

    Tariq Sadad;Amjad Rehman;Asim Munir;Tanzila Saba

  • 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

  • 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

  • Secure and energy-efficient framework using Internet of Medical Things for e-healthcare.

    Tanzila Saba;Khalid Haseeb;Imran Ahmed;Amjad Rehman

  • Detection of copy-move image forgery based on discrete cosine transform

    Mohammed Hazim Alkawaz;Ghazali Sulong;Tanzila Saba;Amjad Rehman

  • 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

  • Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection

    Abdul Majid;Muhammad Attique Khan;Mussarat Yasmin;Amjad Rehman

  • Deep learning model integrating features and novel classifiers fusion for brain tumor segmentation

    Sajid Iqbal;Sajid Iqbal;Muhammad U. Ghani Khan;Tanzila Saba;Zahid Mehmood

  • Brain Tumor Classification Using Meta-Heuristic Optimized Convolutional Neural Networks

    Unknown

  • Content-based image retrieval using PSO and k-means clustering algorithm

    Zeyad Safaa Younus;Zeyad Safaa Younus;Dzulkifli Mohamad;Tanzila Saba;Mohammed Hazim Alkawaz;Mohammed Hazim Alkawaz

  • Detecting Pneumonia Using Convolutions and Dynamic Capsule Routing for Chest X-ray Images

    Ansh Mittal;Deepika Kumar;Mamta Mittal;Tanzila Saba

  • A framework of human detection and action recognition based on uniform segmentation and combination of Euclidean distance and joint entropy-based features selection

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

  • Neural networks for document image preprocessing: state of the art

    Amjad Rehman;Tanzila Saba

  • A Sustainable Deep Learning Framework for Object Recognition Using Multi-Layers Deep Features Fusion and Selection

    Muhammad Rashid;Muhammad Attique Khan;Majed Alhaisoni;Shui-Hua Wang

Frequent Co-Authors

Tanzila Saba
Tanzila Saba Prince Sultan University
Muhammad Attique Khan
Muhammad Attique Khan Prince Mohammad bin Fahd University
Muhammad Sharif
Muhammad Sharif King Fahd University of Petroleum and Minerals
Nadeem Javaid
Nadeem Javaid National Yunlin University of Science and Technology
Muhammad Sharif
Muhammad Sharif COMSATS University Islamabad
Tallha Akram
Tallha Akram Prince Sattam Bin Abdulaziz University
Jaime Lloret
Jaime Lloret Universitat Politècnica de València
Mudassar Raza
Mudassar Raza Namal College
Mussarat Yasmin
Mussarat Yasmin University of Gujrat
Umar Qasim
Umar Qasim University of Alberta

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