9 citations · 17 across the 7 of their papers we have counts for
7 papers
CNN-based Classification Framework for Lung Tissues with Auxiliary Information
Huafeng Hu, Ruijie Ye, Jeyarajan Thiyagalingam +2
Interstitial lung diseases are a large group of heterogeneous diseases characterized by different degrees of alveolitis and pulmonary fibrosis. Accurately diagnosing these diseases…
Sleep Posture One-Shot Learning Framework Using Kinematic Data Augmentation: In-Silico and In-Vivo Case Studies
Omar Elnaggar, Frans Coenen, Andrew Hopkinson +2
Sleep posture is linked to several health conditions such as nocturnal cramps and more serious musculoskeletal issues. However, in-clinic sleep assessments are often limited to vit…
A Robust Framework of Chromosome Straightening with ViT-Patch GAN
Sifan Song, Jinfeng Wang, Fengrui Cheng +9
Chromosomes carry the genetic information of humans. They exhibit non-rigid and non-articulated nature with varying degrees of curvature. Chromosome straightening is an important s…
Bilateral-ViT for Robust Fovea Localization
Sifan Song, Kang Dang, Qinji Yu +4
The fovea is an important anatomical landmark of the retina. Detecting the location of the fovea is essential for the analysis of many retinal diseases. However, robust fovea local…
Do not let the history haunt you -- Mitigating Compounding Errors in Conversational Question Answering
Angrosh Mandya, James O'Neill, Danushka Bollegala +1
The Conversational Question Answering (CoQA) task involves answering a sequence of inter-related conversational questions about a contextual paragraph. Although existing approaches…
Contextualised Graph Attention for Improved Relation Extraction
Angrosh Mandya, Danushka Bollegala, Frans Coenen
This paper presents a contextualized graph attention network that combines edge features and multiple sub-graphs for improving relation extraction. A novel method is proposed to us…
Combining Long Short Term Memory and Convolutional Neural Network for Cross-Sentence n-ary Relation Extraction
Angrosh Mandya, Danushka Bollegala, Frans Coenen +1
We propose in this paper a combined model of Long Short Term Memory and Convolutional Neural Networks (LSTM-CNN) that exploits word embeddings and positional embeddings for cross-s…