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Human Activity Recognition using Multi-Head CNN followed by LSTM
[article]
2020
arXiv
pre-print
This study presents a novel method to recognize human physical activities using CNN followed by LSTM. Achieving high accuracy by traditional machine learning algorithms, (such as SVM, KNN and random forest method) is a challenging task because the data acquired from the wearable sensors like accelerometer and gyroscope is a time-series data. So, to achieve high accuracy, we propose a multi-head CNN model comprising of three CNNs to extract features for the data acquired from different sensors
arXiv:2003.06327v1
fatcat:trdzdtspwvhwteoxeyzzftwy3y