MadhavShashi / Human-Activity-Recognition-Using-Smartphones-Sensor-DataSetLinks
Human activity recognition, is a challenging time series classification task. It involves predicting the movement of a person based on sensor data and traditionally involves deep domain expertise and methods from signal processing to correctly engineer features from the raw data in order to fit a machine learning model.
☆80Updated 4 years ago
Alternatives and similar repositories for Human-Activity-Recognition-Using-Smartphones-Sensor-DataSet
Users that are interested in Human-Activity-Recognition-Using-Smartphones-Sensor-DataSet are comparing it to the libraries listed below
Sorting:
- Multimodal human activity recognition using wrist-worn wearable sensors.☆48Updated 4 years ago
- Transformer for Human Activity Recognition☆71Updated 2 years ago
- Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).☆67Updated 2 years ago
- DeepConvLSTM implemented in python 3 and pytorch☆26Updated 3 years ago
- DeepConvLSTM model for sensor-based human activity recognition in Pytorch☆39Updated 6 years ago
- Data Analysis and Machine Learning on Physical monitoring data☆15Updated 5 years ago
- predicts the human activities based on accelerometer and Gyroscope data of Smart phones☆58Updated 4 years ago
- ☆54Updated 6 years ago
- ☆40Updated 7 years ago
- DANA: Dimension-Adaptive Neural Architecture (UbiComp'21)( ACM IMWUT)☆45Updated 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
- This repository provides the codes and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardizatio…☆103Updated 5 years ago
- Official GitHub page of the best-paper award publication "Improving Deep Learning for HAR with shallow LSTMs" presented at the Internatio…☆55Updated 3 months ago
- Improving Human Activity Recognition through Self-training with Unlabeled Data☆42Updated 3 years ago
- Encoding human activity by considering salient sensors and time points.☆40Updated 2 years ago
- Deep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer …☆23Updated 4 years ago
- Human Activity Recognition Transformer (HART) is a transformer based architecture that has been specifically adapted for IMU sensing devi…☆63Updated 6 months ago
- ☆36Updated 8 years ago
- The MHEALTH (Mobile Health) dataset is devised to benchmark techniques dealing with human behavior analysis based on multimodal body sens…☆20Updated 4 years ago
- CNN, LSTM, CNN+LSTM for human activity recongnition on WISDM dataset(smartphone dataset)☆20Updated 6 years ago
- A research project of applying deep learning models and data fusion algorithms on Human Activity Recognition(HAR)/Activities of Daily Liv…☆19Updated 4 years ago
- Code for our IJCAI 2019 paper "A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition".☆16Updated 5 years ago
- ☆9Updated 6 years ago
- This project senses human activity with the help of an app installed in the smartphone which uses ML to predict from the data collected f…☆14Updated 4 years ago
- Classifying the physical activities performed by a user based on accelerometer and gyroscope sensor data collected by a smartphone in the…☆96Updated 8 years ago
- Multimodal Dataset of Freezing of Gait in Parkinson's Disease☆48Updated 2 years ago
- Intertial-based Human Activity Recognition with Transformers☆77Updated 4 years ago
- A research project that aims to detect Parkinson's disease in patients using Gait Analysis data. Subsequently, the project may make use o…☆62Updated 7 years ago
- Contrastive Learning (SimCLR) for Human Activity Recognition☆77Updated 4 years ago
- An implementation of the CNN-LSTM model for Classifying Time Series Human Activities☆25Updated 4 years ago