Activity Recognition using Temporal Optical Flow Convolutional Features and Multi-Layer LSTM
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Updated
Jun 14, 2021 - C++
Activity Recognition using Temporal Optical Flow Convolutional Features and Multi-Layer LSTM
Auritus: An Open-Source Optimization Toolkit for Training and Development of Human Movement Models and Filters Using Earables
This project is a part of our work, "Dynamic Vision Sensors for Human Activity Recognition" accepted at the IEEE 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017
Human Activity Recognition using wearable sensors. Project @ National University Of Singapore.
Human activity recognition using Machine Learning and using the trained model with an actual device (for prototype I am using nodeMCU here wih GY87 sensor).
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