Theekshana Dissanayake

According to our database, Theekshana Dissanayake authored at least 8 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Multi-stage stacked temporal convolution neural networks (MS-S-TCNs) for biosignal segmentation and anomaly localization.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes

Pattern Recognit., July, 2023

Generalized Generative Deep Learning Models for Biosignal Synthesis and Modality Transfer.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes

IEEE J. Biomed. Health Informatics, February, 2023

2022

Geometric Deep Learning for Subject Independent Epileptic Seizure Prediction Using Scalp EEG Signals.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes

IEEE J. Biomed. Health Informatics, 2022

2021

A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Houman Ghaemmaghami, Clinton Fookes

IEEE J. Biomed. Health Informatics, 2021

Domain Generalization in Biosignal Classification.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Houman Ghaemmaghami, Sridha Sridharan, Clinton Fookes

IEEE Trans. Biomed. Eng., 2021

2020

Patient-independent Epileptic Seizure Prediction using Deep Learning Models.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes

CoRR, 2020

Understanding the Importance of Heart Sound Segmentation for Heart Anomaly Detection.

Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Houman Ghaemmaghami, Clinton Fookes

CoRR, 2020

2019

An Ensemble Learning Approach for Electrocardiogram Sensor Based Human Emotion Recognition.

Theekshana Dissanayake, Yasitha Rajapaksha, Roshan G. Ragel, Isuru Nawinne

Sensors, 2019