guillaume-chevalierHAR-stacked-residual-bidir-LSTMs

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HAR Stacked Residual Bidir LSTMs

The project is based on this repository which is presented as a tutorial. It consists of Human Activity Recognition (HAR) using stacked residual bidirectional-LSTM cells (RNN) with TensorFlow.

Features

Deep Learning Frameworks - Improved recurrent network architecture for activity recognition.

HAR Stacked Residual Bidir LSTMs

Features

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