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cnn-hd-semg-classifier

This is an implementation of gesture recognition using a light weight convolutional neural network (CNN) - MobilenetV2. The recognition is based on high-density surface electromyography (HD-sEMG) signals from two datasets: CSL HD-sEMG and ICE Lab HD-sEMG.

cnn-pruning-engine

cnn-training-pytorch-cifar

95+ Acc on Cifar10, 70+ Acc on Cifar100

drome-jointangleestimation

exoglovescvfusion

ieee-ner-2023-effie

[IEEE NER 2023] EffiE: Efficient Convolutional Neural Network for Real-Time EMG Pattern Recognition System on Edge Devices

ieee-ner-2023-rohde

[IEEE NER 2023] Toward Robust High-Density EMG Pattern Recognition using Generative Adversarial Network and Convolutional Neural Network Implementation

kmean-ofa--pruning

Once For All Implementation with K-Means Clustering Algorithm

mmyohmi-real-time-emg-on-mobile

on-device-computer-vsion-cnn

Efficient Deployment Of Deep Learning Model On Cortex-M Based Microcontrollers Using Deep Compression

on-device-keywords-spotting

prosthetic_hand_control_mqtt_ssdmobilenet

real-time-bionic-arm-control-via-cnn-on-sony-spresense

similarity-aware-training