AIlibraryPython

HAR-stacked-residual-bidir-LSTMs

Using deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.

323 stars97 forks3 issuesApache-2.0更新于 2026/4/24

GitHub 仓库项目官网

bidirectional-lstm-cellshuman-activity-recognitionlstmresidual-layersresidual-lstm-cellsrnnstacked-layerstensorflow

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