David M. Burns

According to our database, David M. Burns authored at least 9 papers between 2018 and 2023.

Collaborative distances:

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

2023

Physiotherapy Exercise Classification with Single-Camera Pose Detection and Machine Learning.

Colin Arrowsmith, David M. Burns, Thomas Mak, Michael R. Hardisty, Cari M. Whyne

Sensors, 2023

2022

Shoulder Physiotherapy Activity Recognition 9-Axis Dataset.

Philip Boyer, David M. Burns, Cari M. Whyne

Dataset, December, 2022

Multi-Modal Deep Learning for Assessing Surgeon Technical Skill.

Kevin Kasa, David M. Burns, Mitchell G. Goldenberg, Omar Selim, Cari M. Whyne, Michael R. Hardisty

Sensors, 2022

Personalized Activity Recognition with Deep Triplet Embeddings.

David M. Burns, Philip Boyer, Colin Arrowsmith, Cari M. Whyne

Sensors, 2022

Bullseye EVD: preclinical evaluation of an intra-procedural system to confirm external ventricular drainage catheter positioning.

Adam Hopfgartner, David M. Burns, Suganth Suppiah, Allan R. Martin, Michael R. Hardisty, Cari M. Whyne

Int. J. Comput. Assist. Radiol. Surg., 2022

2021

Out-of-Distribution Detection of Human Activity Recognition with Smartwatch Inertial Sensors.

Philip Boyer, David M. Burns, Cari M. Whyne

Sensors, 2021

2020

Personalized Activity Recognition with Deep Triplet Embeddings.

David M. Burns, Cari M. Whyne

CoRR, 2020

2018

Seglearn: A Python Package for Learning Sequences and Time Series.

David M. Burns, Cari M. Whyne

J. Mach. Learn. Res., 2018

Shoulder Physiotherapy Exercise Recognition: Machine Learning the Inertial Signals from a Smartwatch.

David M. Burns, Nathan Leung, Michael R. Hardisty, Cari M. Whyne, Patrick Henry, Stewart McLachlin

CoRR, 2018