Name: MIC-Lab
Type: User
Company: San Francisco State University
Bio: The MIC Lab at SFSU performs research in efficient mobile computing, deep learning acceleration, and intelligent application development.
Location: San Francisco
Blog: http://sfsu-miclab.org/
MIC-Lab's Projects
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.
95+ Acc on Cifar10, 70+ Acc on Cifar100
[IEEE NER 2023] EffiE: Efficient Convolutional Neural Network for Real-Time EMG Pattern Recognition System on Edge Devices
[IEEE NER 2023] Toward Robust High-Density EMG Pattern Recognition using Generative Adversarial Network and Convolutional Neural Network Implementation
Once For All Implementation with K-Means Clustering Algorithm
Object Detection Fine tune
Efficient Deployment Of Deep Learning Model On Cortex-M Based Microcontrollers Using Deep Compression