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Heterogeneous multi-modal sensor fusion with hybrid attention for exercise recognition. (2020)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N. and COOPER, K. [2020]. Heterogeneous multi-modal sensor fusion with hybrid attention for exercise recognition. To be presented at the 2020 Institute of Electrical and Electronics Engineers (IEEE) World computational intelligence congress (WCCI 2020), co-located with 2020 International Joint Conference on Neural Networks (IJCNN 2020), 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2020), and IEEE Congress on Evolutionary Computation (IEEE CEC 2020), 19-24 July 2020, Glasgow, UK.

Exercise adherence is a key component of digital behaviour change interventions for the self-management of musculoskeletal pain. Automated monitoring of exercise adherence requires sensors that can capture patients performing exercises and Machine Le... Read More about Heterogeneous multi-modal sensor fusion with hybrid attention for exercise recognition..

Human activity recognition with deep metric learners. (2020)
Conference Proceeding
MARTIN, K., WIJEKOON, A. and WIRATUNGA, N. 2019. Human activity recognition with deep metric learners. In Kapetanakis, S. and Borck, H. (eds.) Workshop proceedings of the 27th International conference on case-based reasoning (ICCBR 2019), 8-12 September 2019, Otzenhausen, Germany. CEUR Workshop Proceedings, 2567. Aachen: CEUR workshop proceedings [online], pages 8-17. Available from: http://ceur-ws.org/Vol-2567/paper1.pdf

Establishing a strong foundation for similarity-based return is a top priority in Case-Based Reasoning (CBR) systems. Deep Metric Learners (DMLs) are a group of neural network architectures which learn to optimise case representations for similarity-... Read More about Human activity recognition with deep metric learners..


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