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[IEEE JBHI 2021] The convolutional neural networks training with Channel-Selectivity for human activity recognition based on sensors
Respository for accelerometer and labels data from unimib-shar dataset
Reinforcement learning with musculoskeletal models
NeurIPS 2018: AI for Prosthetics Challenge – 3rd place solution
Apply Reinforcement Learning (RL) to enable prosthetics to calibrate with differences between humans and differences between walking environments
Reinforcement learning environments with musculoskeletal models
Deep Learning-Based Gait Recognition Using Smartphones in the Wild
A tutorial for using deep learning for activity recognition (Pytorch and Tensorflow)
This is the companion repository for our paper iSPLInception: Redefining the State-of-the-Art for Human Activity Recognition which will be published in IEEE Access - 2021.
The layer-wise training convolutional neural networks using local loss for sensor based human activity recognition
The layer-wise training convolutional neural networks using local loss for sensor based human activity recognition
An 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 bas…
PyTorch implementation of the U-Net for image semantic segmentation with high quality images