Machine vision for the quality assessment of emulsions in pharmaceutical processing. - Saritha Unnikrishnan; John Donovan; Russell Macpherson; David Tormey (UV, 2018)

An Integrated Histogram-Based Vision and Machine-Learning Classification Model for Industrial Emulsion Processing. - Saritha Unnikrishnan; John Donovan; Russell Macpherson; David Tormey (IEEE Trans. Ind. Informatics, 2020)

A Hybrid Deep Model for Brain Tumor Classification. - Hamail Ayaz; Muhammad Ahmad; David Tormey; Ian McLoughlin; Saritha Unnikrishnan (MICAD, 2021)

Hyperspectral Brain Tissue Classification using a Fast and Compact 3D CNN Approach. - Hamail Ayaz; David Tormey; Ian McLoughlin; Muhammad Ahmad; Saritha Unnikrishnan (IPAS, 2022)

Lightweight Deep Learning for Breast Cancer Diagnosis Based on Slice Selection Techniques. - Oladosu Oladimeji; Hamail Ayaz; Ian McLoughlin; Saritha Unnikrishnan (AICS, 2023)

A random graph-based neural network approach to assess glioblastoma progression from perfusion MRI. - Hamail Ayaz; Hanieh Khosravi; Ian McLoughlin; David Tormey; Yelda Özsunar; Saritha Unnikrishnan (Biomed. Signal Process. Control., 2023)

Optimizing BI-RADS 4 Lesion Assessment Using Lightweight Convolutional Neural Network with CBAM in Contrast Enhanced Mammography. - Oladosu Oladimeji; Hamail Ayaz; Ian McLoughlin; Saritha Unnikrishnan (Deep-Breath@MICCAI, 2024)

A Dual Modular Clock Algorithm for Cognitive Radio-based Emergency Response Network. - Zahid Ali; Saim Ghafoor; Saritha Unnikrishnan; Eoghan Furey; Ian McLoughlin (CCNC, 2025)

Post-hoc eXplainable AI methods for analyzing medical images of gliomas ( - A review for clinical applications). - Hamail Ayaz; Esra Sümer; Esin Ozturk-Isik; Thomas C. Booth; David Tormey; Ian McLoughlin; Saritha Unnikrishnan (Comput. Biol. Medicine, 2025)

Deep learning advances in breast medical imaging with a focus on clinical readiness and radiologists' perspective. - Oladosu Oladimeji; Abdullah-Al-Zubaer Imran; Xiaoqin Wang; Saritha Unnikrishnan (Image Vis. Comput., 2025)