A LSTM and CNN Based Assemble Neural Network Framework for Arrhythmias Classification

Full text for this resource is not available from the Research Repository.

Liu, Fan, Zhou, X, Cao, J, Wang, Z, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2019) A LSTM and CNN Based Assemble Neural Network Framework for Arrhythmias Classification. In: 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), 12 May 2019 - 17 May 2019, Brighton, United Kingdom.

Item type Conference or Workshop Item (Paper)
URI http://vuir.vu.edu.au/id/eprint/39315
Identification Number https://doi.org/10.1109/ICASSP.2019.8682299
Official URL https://ieeexplore.ieee.org/document/8682299
ISBN 9781479981311
Subjects Current > FOR Classification > 0906 Electrical and Electronic Engineering
Current > Division/Research > College of Science and Engineering
Keywords long short-term memory network; convolutional neural network; arrhythmias; classification model; stacked bidirectional long shotterm memory network; two-dimensional convolutional neural network; ensemble empirical mode decomposition
Citations in Scopus 7 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login