H27: Deep Learning for Brain-Machine Interface (DL-BMI)

Paper Submission for H27

SMC2018:H27 submission site (external site)

Abstracts

Deep learning has achieved great success in image and video analysis, natural language processing, speech recognition, etc., and recently has also started to find applications in brain- machine interfaces, evidenced by multiple deep learning papers presented at BMI 2017. In fact, we organized a special session on “Machine Learning and Signal Processing for Brain and Neural Computer Interfaces” at BMI 2017. It attracted many submissions, and eventually it was broken into three special sessions to accommodate them. The first special session was dedicated to deep learning. So, this year we propose a dedicated special session on deep learning for BMI. The topics include, but are not limited to: -Convolutional neural networks for BMIDeep feedforward networks for BMI Deep belief networks for BMI Deep residual networks for BMI Extreme learning machines for BMI Generative adversarial networks for BMI Long short term memory for BMI Recurrent neural networks for BMI.

Session Chairs