lingjuanlv / LSTM-CNN-model-for-HAR
LSTM-CNN model for Human Activity Recognition
☆23Updated 6 years ago
Alternatives and similar repositories for LSTM-CNN-model-for-HAR:
Users that are interested in LSTM-CNN-model-for-HAR are comparing it to the libraries listed below
- Human activity recognition(LSTM, BidLSTM, BidLSTM+CNN, LSTM+CNN)☆15Updated 6 years ago
- CNN, LSTM, CNN+LSTM for human activity recongnition on WISDM dataset(smartphone dataset)☆20Updated 6 years ago
- AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors☆28Updated 6 years ago
- ☆40Updated 7 years ago
- Comparison of frequently used deep learning architectures (LSTM, biLSTM, GRU and CNN) on ten Human Activity Recognition datasets.☆17Updated last year
- Classifying the physical activities performed by a user based on accelerometer and gyroscope sensor data collected by a smartphone in the…☆95Updated 7 years ago
- Use a LSTM network to predict human activities from sensor signals collected from a smartphone☆49Updated 2 years ago
- Code for our IJCAI 2019 paper "A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition".☆16Updated 4 years ago
- Encoding human activity by considering salient sensors and time points.☆40Updated last year
- DeepConvLSTM model for sensor-based human activity recognition in Pytorch☆39Updated 5 years ago
- Simple 1D CNN approach to human-activity-recognition (HAR) in PyTorch.☆56Updated 5 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 7 years ago
- ☆8Updated 4 years ago
- Artificial Neural Networks (ANN), k-Nearest Neighbors, Random Forest classifier and Support Vector Machines (SVM) were trained over a HAR…☆24Updated 6 years ago
- Human Activity Recognition Using Deep Learning☆48Updated 5 years ago
- ☆36Updated 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…☆84Updated 6 years ago
- Improving Human Activity Recognition through Self-training with Unlabeled Data☆39Updated 3 years ago
- Code for the paper "Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation", Buffelli D., Vandin F.,…☆18Updated 3 years ago
- 3-layer-CNN and ResNet with OPPORTUNITY dataset, PAMAP2 dataset, UCI-HAR dataset, UniMiB-SHAR dataset, USC-HAD dataset, and WISDM dataset…☆51Updated 2 years ago
- [ECAI 2020] Tensorflow 2.x Implementation of "Human Activity Recognition from Wearable Sensor Data Using Self-Attention"☆48Updated 3 years ago
- predicts the human activities based on accelerometer and Gyroscope data of Smart phones☆58Updated 3 years ago
- This repository provides the codes and data used in our paper "Human Activity Recognition Based on Wearable Sensor Data: A Standardizatio…☆100Updated 5 years ago
- Attend and Discriminate: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors☆23Updated 3 years ago
- An implementation of the CNN-LSTM model for Classifying Time Series Human Activities☆23Updated 4 years ago
- This is the project of "If-ConvTransformer: A Framework for Human Activity Recognition Using IMU Fusion and ConvTransformer"☆33Updated last year
- The layer-wise training convolutional neural networks using local loss for sensor based human activity recognition☆20Updated 4 years ago
- DeepConvLSTM implemented in python 3 and pytorch☆24Updated 3 years ago
- Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).☆63Updated 2 years ago
- CNNs and Stacked denoising autoencoders for human activity recognition using Keras☆22Updated 6 years ago