22 citations · 37 across the 6 of their papers we have counts for
6 papers
Unimodal Intermediate Training for Multimodal Meme Sentiment Classification
Muzhaffar Hazman, Susan McKeever, Josephine Griffith
Internet Memes remain a challenging form of user-generated content for automated sentiment classification. The availability of labelled memes is a barrier to developing sentiment c…
Meme Sentiment Analysis Enhanced with Multimodal Spatial Encoding and Facial Embedding
Muzhaffar Hazman, Susan McKeever, Josephine Griffith
Internet memes are characterised by the interspersing of text amongst visual elements. State-of-the-art multimodal meme classifiers do not account for the relative positions of the…
Exploring the Impact of Noise and Degradations on Heart Sound Classification Models
Davoud Shariat Panah, Andrew Hines, Susan McKeever
The development of data-driven heart sound classification models has been an active area of research in recent years. To develop such data-driven models in the first place, heart s…
Wider Vision: Enriching Convolutional Neural Networks via Alignment to External Knowledge Bases
Xuehao Liu, Sarah Jane Delany, Susan McKeever
Deep learning models suffer from opaqueness. For Convolutional Neural Networks (CNNs), current research strategies for explaining models focus on the target classes within the asso…
Feature Fusion of Raman Chemical Imaging and Digital Histopathology using Machine Learning for Prostate Cancer Detection
Trevor Doherty, Susan McKeever, Nebras Al-Attar +10
The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accu…
Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance Propagation
hsan Ullah, Andre Rios, Vaibhav Gala +1
Trust and credibility in machine learning models is bolstered by the ability of a model to explain itsdecisions. While explainability of deep learning models is a well-known challe…