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Tariq Rahim

Senior Lecturer

Kingston University

United Kingdom

Research Interests

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About

Dr. Tariq Rahim is a Lecturer at Kingston University in the United Kingdom. His research focuses on advanced machine learning applications in medical imaging, blockchain technology, and the Internet of Battlefield Things. He has contributed to the field through several recent articles, including work on automated diagnosis of otitis media and compressive sampling techniques for medical images.

Articles (11)

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2026

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2026

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2025

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2024

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2024

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2022

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2022

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2021

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2021

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2021

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2021

Collaborators (4)

Muhammad Arslan Usman

Senior Lecturer / Assisstant Professor

Kingston University

UNITED KINGDOM

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Fei Zhao

Professor in Hearing Science and Audiology

Cardiff University

UNITED KINGDOM

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Nada Philip

Professor

Kingston University

UNITED KINGDOM

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Aamir Raja

Associate Professor

University of Otago

NEW ZEALAND

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Tariq Rahim

Research Interests

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Articles (11)

Detecting Hate Speech in Hindi Digital Discourse Using Transformer–Long Short-Term Memory Models

Edge-guided ControlNet synthetic chest x-ray augmentation and ensemble classification

A multimodal machine learning framework for diagnosis of otitis media with effusion using 3D wideband acoustic immittance

An advanced machine learning approach for high accuracy automated diagnosis of otitis media with effusion in different age groups using 3D wideband acoustic immittance

UAV-Employed Intelligent Approach to Identify Injured Soldier on Blockchain-Integrated Internet of Battlefield Things

Basis Pursuit With Sparsity Averaging for Compressive Sampling of Iris Images

Compressive Sampling of Color Retinal Image Using Spread Spectrum Fourier Sampling and Total Variant

RGB-Based Compressed Medical Imaging Using Sparsity Averaging Reweighted Analysis for Wireless Capsule Endoscopy Images

Exploiting De-Noising Convolutional Neural Networks DnCNNs for an Efficient Watermarking Scheme: A Case for Information Retrieval

Compressed medical imaging based on average sparsity model and reweighted analysis of multiple basis pursuit

Total Variant Based Average Sparsity Model With Reweighted Analysis for Compressive Sensing of Computed Tomography

Collaborators (4)

Muhammad Arslan Usman

Fei Zhao

Nada Philip

Aamir Raja

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