activity
20172022
most citedSoft + Hardwired Attention: An LSTM Framework for Human Trajectory Prediction and Abnormal Event Detection

19 citations · 44 across the 10 of their papers we have counts for

collaborators

23 papers

cs.CV2022

Using Auxiliary Information for Person Re-Identification -- A Tutorial Overview

Tharindu Fernando, Clinton Fookes, Sridha Sridharan +1

Person re-identification (re-id) is a pivotal task within an intelligent surveillance pipeline and there exist numerous re-id frameworks that achieve satisfactory performance in ch…

eess.IV2021

Multi-Slice Net: A novel light weight framework for COVID-19 Diagnosis

Harshala Gammulle, Tharindu Fernando, Sridha Sridharan +2

This paper presents a novel lightweight COVID-19 diagnosis framework using CT scans. Our system utilises a novel two-stage approach to generate robust and efficient diagnoses acros…

cs.SD2021

Robust and Interpretable Temporal Convolution Network for Event Detection in Lung Sound Recordings

Tharindu Fernando, Sridha Sridharan, Simon Denman +2

This paper proposes a novel framework for lung sound event detection, segmenting continuous lung sound recordings into discrete events and performing recognition on each event. Exp…

cs.LG2020

Deep Learning for Medical Anomaly Detection -- A Survey

Tharindu Fernando, Harshala Gammulle, Simon Denman +2

Machine learning-based medical anomaly detection is an important problem that has been extensively studied. Numerous approaches have been proposed across various medical applicatio…

cs.CV20207 cited

Patient-independent Epileptic Seizure Prediction using Deep Learning Models

Theekshana Dissanayake, Tharindu Fernando, Simon Denman +2

Objective: Epilepsy is one of the most prevalent neurological diseases among humans and can lead to severe brain injuries, strokes, and brain tumors. Early detection of seizures ca…

cs.CV2020

Domain Generalization in Biosignal Classification

Theekshana Dissanayake, Tharindu Fernando, Simon Denman +3

Objective: When training machine learning models, we often assume that the training data and evaluation data are sampled from the same distribution. However, this assumption is vio…