arturjordao / WearableSensorData
This repository provides the codes and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art", where we implement and evaluate several state-of-the-art approaches, ranging from handcrafted-based methods to convolutional neural networks.
☆100Updated 5 years ago
Alternatives and similar repositories for WearableSensorData:
Users that are interested in WearableSensorData are comparing it to the libraries listed below
- ☆40Updated 7 years ago
- Encoding human activity by considering salient sensors and time points.☆40Updated last year
- DeepConvLSTM implemented in python 3 and pytorch☆26Updated 3 years ago
- Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).☆63Updated 2 years ago
- Multimodal human activity recognition using wrist-worn wearable sensors.☆46Updated 4 years ago
- DeepConvLSTM model for sensor-based human activity recognition in Pytorch☆39Updated 5 years ago
- Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors☆23Updated 4 years ago
- AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors☆28Updated 6 years ago
- Transformer for Human Activity Recognition☆70Updated 2 years ago
- Package for analyzing human motion data (e.g. PA, gait)☆90Updated 5 months ago
- Official GitHub page of the best-paper award publication "Improving Deep Learning for HAR with shallow LSTMs" presented at the Internatio…☆51Updated 4 months ago
- Improving Human Activity Recognition through Self-training with Unlabeled Data☆40Updated 3 years ago
- Code for HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data, IEEE PerCom CoMoRea 2022☆13Updated 2 years ago
- [ECAI 2020] Tensorflow 2.x Implementation of "Human Activity Recognition from Wearable Sensor Data Using Self-Attention"☆48Updated 3 years ago
- DANA: Dimension-Adaptive Neural Architecture (UbiComp'21)( ACM IMWUT)☆45Updated 3 years ago
- Classifying the physical activities performed by a user based on accelerometer and gyroscope sensor data collected by a smartphone in the…☆96Updated 7 years ago
- Contrastive Learning (SimCLR) for Human Activity Recognition☆75Updated 3 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…☆84Updated 6 years ago
- ☆36Updated 8 years ago
- Ensembles of Deep LSTM Learners for Human Activity Recognition using Wearables in Pytorch☆13Updated 5 years ago
- Human Activity Recognition Transformer (HART) is a transformer based architecture that has been specifically adapted for IMU sensing devi…☆57Updated 3 months ago
- ☆8Updated 6 years ago
- Comparison of frequently used deep learning architectures (LSTM, biLSTM, GRU and CNN) on ten Human Activity Recognition datasets.☆17Updated last year
- MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and …☆334Updated 3 years ago
- CAPTURE-24: Human activity recognition with activity trackers☆30Updated 4 months ago
- CNN, LSTM, CNN+LSTM for human activity recongnition on WISDM dataset(smartphone dataset)☆20Updated 6 years ago
- Human activity recognition, is a challenging time series classification task. It involves predicting the movement of a person based on se…☆75Updated 4 years ago
- Use a LSTM network to predict human activities from sensor signals collected from a smartphone☆49Updated 2 years ago
- Human Activity Recognition Using Deep Learning☆48Updated 5 years ago
- Code for our IJCAI 2019 paper "A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition".☆16Updated 5 years ago