Abdul Razaque Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Professor

Arkansas Tech University

faculty

30 h-index 249 pubs 3,144 cited

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Biography and Research Information

OverviewAI-generated summary

Abdul Razaque's research interests encompass the application of artificial intelligence and machine learning techniques to address challenges across various domains. He has investigated deep learning frameworks for tasks such as unmanned aerial vehicles detection and cyberbullying detection on social media. His work also includes exploring improved Support Vector Machine methods for remote sensing image classification.

Razaque has also focused on the integration of advanced technologies within industrial contexts, examining the role of technologies in Industry 4.0. His research extends to the cybersecurity of emerging networks, including studies on blockchains for the Internet of Vehicles and DDoS detection in 5G-enabled IoT networks. He has also contributed to research on energy-efficient and secure mobile fog-based cloud computing for the Internet of Things.

Furthermore, his research portfolio includes a review of artificial intelligence methods for Alzheimer's disease diagnosis, drawing insights from neuroimaging to sensor data analysis. Razaque holds a h-index of 30 with over 249 publications and 3,144 citations. He has collaborated with Hari Mohan on multiple publications.

Metrics

  • h-index: 30
  • Publications: 249
  • Citations: 3,144

Selected Publications

  • Blockchain-Enabled Smart Contracts and Prioritized Delegated Proof-of-Stake Paradigm for Secure and Scalable Electronic Voting Systems (2025) DOI
  • Enhancing Pharmaceutical Supply Chain Transparency and Security with Blockchain and Big Data Integration (2025) DOI
  • A reinforcement learning and predictive analytics approach for enhancing credit assessment in manufacturing (2025) DOI
  • Review of malicious code detection in data mining applications: challenges, algorithms, and future direction (2025) DOI
  • Advanced Segmentation of Gastrointestinal (GI) Cancer Disease Using a Novel U-MaskNet Model (2024) DOI
  • Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques (2024) DOI
  • A depth analysis of recent innovations in non-invasive techniques using artificial intelligence approach for cancer prediction (2024) DOI
  • Designing an Intelligent Scoring System for Crediting Manufacturers and Importers of Goods in Industry 4.0 (2024) DOI
  • Blockchain-enabled heterogeneous 6G supported secure vehicular management system over cloud edge computing (2024) DOI
  • A review of artificial intelligence methods for Alzheimer's disease diagnosis: Insights from neuroimaging to sensor data analysis (2024) DOI
  • Deep learning for unmanned aerial vehicles detection: A review (2024) DOI
  • Efficient Internet-of-Things Cyberattack Depletion Using Blockchain-Enabled Software-Defined Networking and 6G Network Technology (2023) DOI
  • Developing Robotic Process Automation to Efficiently Integrate Long-Term Business Process Management (2023) DOI
  • Quantum communication networks: Design, reliability, and security (2023) DOI
  • ESOA-HGRU: egret swarm optimization algorithm-based hybrid gated recurrent unit for classification of diabetic retinopathy (2023) DOI

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