Kay Cooper

Orcid: 0000-0001-9958-2511

According to our database1, Kay Cooper authored at least 14 papers between 2016 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2020
A knowledge-light approach to personalised and open-ended human activity recognition.
Knowl. Based Syst., 2020

FitChat: Conversational Artificial Intelligence Interventions for Encouraging Physical Activity in Older Adults.
CoRR, 2020

Heterogeneous Multi-Modal Sensor Fusion with Hybrid Attention for Exercise Recognition.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Learning to Compare with Few Data for Personalised Human Activity Recognition.
Proceedings of the Case-Based Reasoning Research and Development, 2020

Learning to Recognise Exercises in the Self-Management of Low Back Pain.
Proceedings of the Thirty-Third International Florida Artificial Intelligence Research Society Conference, 2020

2019
MEx - Multi-modal Exercise Dataset.
Dataset, October, 2019

Dataset, September, 2019

MEx: Multi-modal Exercises Dataset for Human Activity Recognition.
CoRR, 2019

2018
Matching networks for personalised human activity recognition.
Proceedings of the First Joint Workshop on AI in Health organized as part of the Federated AI Meeting (FAIM 2018), 2018

Improving kNN for Human Activity Recognition with Privileged Learning Using Translation Models.
Proceedings of the Case-Based Reasoning Research and Development, 2018

Personalised Human Activity Recognition Using Matching Networks.
Proceedings of the Case-Based Reasoning Research and Development, 2018

2017
Learning Deep and Shallow Features for Human Activity Recognition.
Proceedings of the Knowledge Science, Engineering and Management, 2017

kNN Sampling for Personalised Human Activity Recognition.
Proceedings of the Case-Based Reasoning Research and Development, 2017

2016
SELFBACK - Activity Recognition for Self-management of Low Back Pain.
Proceedings of the Research and Development in Intelligent Systems XXXIII, 2016


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