AlphaUncommon
guillaume-chevalier/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.
- Owner
- guillaume-chevalier (personal account)
- Stars
- Stars: 322
- Forks
- Forks: 96
- Language
- Python
- License
- Apache-2.0
- Created
- 2016
- Topics
- tensorflowlstmrnnstacked-layersresidual-layersresidual-lstm-cellsbidirectional-lstm-cellshuman-activity-recognition
- Tier
- Alpha (250 to 699 ★) What this tier means
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