Harmonic Loss Function for Sensor-Based Human Activity Recognition Based on LSTM Recurrent Neural Networks
Human activity recognition (HAR) has been a very popular field in both real practice and theoretical research.Over the years, a number of many-vs-one Long Short-Term Memory (LSTM) models have been proposed for the sensor-based HAR problem.However, how to utilize sequence outputs of them to improve the HAR performance has not been studied seriously.