S-Convnet: A Shallow Convolutional Neural Network Architecture for Neuromuscular Activity Recognition Using Instantaneous High-Density Surface EMG Images

Md. Rabiul Islam 0004, Daniel Massicotte, François Nougarou, Philippe Massicotte, Wei-Ping Zhu. S-Convnet: A Shallow Convolutional Neural Network Architecture for Neuromuscular Activity Recognition Using Instantaneous High-Density Surface EMG Images. In 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2020, Montreal, QC, Canada, July 20-24, 2020. pages 744-749, IEEE, 2020. [doi]

@inproceedings{IslamMNMZ20,
  title = {S-Convnet: A Shallow Convolutional Neural Network Architecture for Neuromuscular Activity Recognition Using Instantaneous High-Density Surface EMG Images},
  author = {Md. Rabiul Islam 0004 and Daniel Massicotte and François Nougarou and Philippe Massicotte and Wei-Ping Zhu},
  year = {2020},
  doi = {10.1109/EMBC44109.2020.9175266},
  url = {https://doi.org/10.1109/EMBC44109.2020.9175266},
  researchr = {https://researchr.org/publication/IslamMNMZ20},
  cites = {0},
  citedby = {0},
  pages = {744-749},
  booktitle = {42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2020, Montreal, QC, Canada, July 20-24, 2020},
  publisher = {IEEE},
  isbn = {978-1-7281-1990-8},
}