Lstm Human Activity RecognitionHuman Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
KCCKernel Cross-Correlator (KCC) for Tracking and Recognition (AAAI 2018)
HARRecognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.
WearableSensorDataThis 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.
Robust-Deep-Learning-PipelineDeep Convolutional Bidirectional LSTM for Complex Activity Recognition with Missing Data. Human Activity Recognition Challenge. Springer SIST (2020)
Human Activity RecognitionA new and computationally cheap method to perform human activity recognition using PoseNet and LSTM. Where we use PoseNet for Preprocessing and LSTM for understand the sequence.
danaDANA: Dimension-Adaptive Neural Architecture (UbiComp'21)( ACM IMWUT)
lstm harLSTM based human activity recognition using smart phone sensor dataset
Human-Activity-RecognitionHuman activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).
dl-for-harOfficial GitHub page of the best-paper award publication "Improving Deep Learning for HAR with shallow LSTMs" presented at the International Symposium on Wearable Computers 21' (ISWC 21')
Awesome-Human-Activity-RecognitionAn up-to-date & curated list of Awesome IMU-based Human Activity Recognition(Ubiquitous Computing) papers, methods & resources. Please note that most of the collections of researches are mainly based on IMU data.
har-wisdm-lstm-rnnsHuman Activity Recognition on the Wireless Sensor Data Mining (WISDM) dataset using LSTM Recurrent Neural Networks