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20212023
most citedA Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysis

7 citations · 16 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2023

InceptionCaps: A Performant Glaucoma Classification Model for Data-scarce Environment

Gyanendar Manohar, Ruairi O'Reilly

Glaucoma is an irreversible ocular disease and is the second leading cause of visual disability worldwide. Slow vision loss and the asymptomatic nature of the disease make its diag…

eess.IV2023★ 2 cited

Adaptive Input-image Normalization for Solving the Mode Collapse Problem in GAN-based X-ray Images

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adversarial Networks play a key role in addressing this imbalance by enabling the gen…

eess.IV2023★ 3 cited

Assessing Intra-class Diversity and Quality of Synthetically Generated Images in a Biomedical and Non-biomedical Setting

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

In biomedical image analysis, data imbalance is common across several imaging modalities. Data augmentation is one of the key solutions in addressing this limitation. Generative Ad…

eess.IV2022

A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesis

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

Imbalanced image datasets are commonly available in the domain of biomedical image analysis. Biomedical images contain diversified features that are significant in predicting targe…

eess.IV2022

Evaluating the Quality and Diversity of DCGAN-based Generatively Synthesized Diabetic Retinopathy Imagery

Cristina-Madalina Dragan, Muhammad Muneeb Saad, Mubashir Husain Rehmani +1

Publicly available diabetic retinopathy (DR) datasets are imbalanced, containing limited numbers of images with DR. This imbalance contributes to overfitting when training machine…

cs.CY2022

Classification of Stress via Ambulatory ECG and GSR Data

Zachary Dair, Muhammad Muneeb Saad, Urja Pawar +2

In healthcare, detecting stress and enabling individuals to monitor their mental health and wellbeing is challenging. Advancements in wearable technology now enable continuous phys…

cs.HC2022

Inter and Intra Signal Variance in Feature Extraction and Classification of Affective State

Zachary Dair, Samantha Dockray, Ruairi O'Reilly

Psychophysiology investigates the causal relationship of physiological changes resulting from psychological states. There are significant challenges with machine learning-based mom…

eess.IV2022

Addressing the Intra-class Mode Collapse Problem using Adaptive Input Image Normalization in GAN-based X-ray Images

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adversarial Networks play a key role in addressing this imbalance by enabling the gen…

cs.LG2022★ 7 cited

A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysis

Muhammad Muneeb Saad, Ruairi O'Reilly, Mubashir Husain Rehmani

In biomedical image analysis, the applicability of deep learning methods is directly impacted by the quantity of image data available. This is due to deep learning models requiring…

cs.SD2021★ 4 cited

Linguistic and Gender Variation in Speech Emotion Recognition using Spectral Features

Zachary Dair, Ryan Donovan, Ruairi O'Reilly

This work explores the effect of gender and linguistic-based vocal variations on the accuracy of emotive expression classification. Emotive expressions are considered from the pers…