guillaume-chevalier / HAR-stacked-residual-bidir-LSTMsLinks
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.
☆321Updated 2 years ago
Alternatives and similar repositories for HAR-stacked-residual-bidir-LSTMs
Users that are interested in HAR-stacked-residual-bidir-LSTMs are comparing it to the libraries listed below
Sorting:
- Deep learning framework for wearable activity recognition based on convolutional and LSTM recurretn layers☆281Updated 7 years ago
- Convolutional Neural Network for Human Activity Recognition in Tensorflow☆482Updated 2 years ago
- AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors☆29Updated 7 years ago
- Convolutional and LSTM networks to classify human activity☆463Updated 6 years ago
- Deepsense: a unified deep learning framework for time-series mobile sensing data processing.☆198Updated 6 years ago
- iPython notebook and Android app that shows how to build LSTM model in TensorFlow and deploy it on Android☆195Updated 4 years ago
- ☆41Updated 8 years ago
- A tutorial for using deep learning for activity recognition (Pytorch and Tensorflow)☆230Updated 3 years ago
- Classifying the physical activities performed by a user based on accelerometer and gyroscope sensor data collected by a smartphone in the…☆98Updated 8 years ago
- MATLAB Human Activity Recognition Toolbox☆57Updated 7 months ago
- Deep convolutional neural network for human activity recognition☆22Updated 7 years ago
- LSTM-CNN model for Human Activity Recognition☆23Updated 7 years ago
- Code repository for experiments on deep architecture for HAR in ubicomp☆25Updated 8 years ago
- An LSTM for time-series classification☆417Updated 7 years ago
- Human activity recognition using hidden Markov model.☆10Updated 7 years ago
- Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification☆141Updated 6 years ago
- This repository provides the codes and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardizatio…☆102Updated 5 years ago
- Temporal Segments LSTM and Temporal-Inception for Activity Recognition☆445Updated 5 years ago
- Code for data processing used for the experiment in paper "Deepsense: a unified deep learning framework for time-series mobile sensing da…☆29Updated 8 years ago
- Artificial Neural Networks (ANN), k-Nearest Neighbors, Random Forest classifier and Support Vector Machines (SVM) were trained over a HAR…☆24Updated 7 years ago
- deadskull7 / Human-Activity-Recognition-with-Neural-Network-using-Gyroscopic-and-Accelerometer-variablesThe VALIDATION ACCURACY is BEST on KAGGLE. Artificial Neural Network with a validation accuracy of 97.98 % and a precision of 95% was ach…☆85Updated 7 years ago
- TensorFlow LSTM-autoencoder implementation☆191Updated 7 years ago
- girishp92 / Human-activity-recognition-using-Recurrent-Neural-Nets-RNN-LSTM-and-Tensorflow-on-SmartphonesThis was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learnin…☆85Updated 8 years ago
- ☆295Updated 8 years ago
- Use a LSTM network to predict human activities from sensor signals collected from a smartphone☆52Updated 3 years ago
- ☆36Updated 8 years ago
- ☆64Updated 2 years ago
- A tensorflow implementation of GAN ( exactly InfoGAN or Info GAN ) to one dimensional ( 1D ) time series data.☆300Updated last year
- Keras implementation of Human Action Recognition for the data set State Farm Distracted Driver Detection (Kaggle)☆181Updated 9 years ago
- Unsupervised Learning of Video Representations using LSTMs☆362Updated 7 years ago