A novel convolutional neural network for deep-learning classification
Newsroom Home Astronomy Biomedical Optics & Medical Imaging Defense & Security Electronic Imaging & Signal Processing Illumination & Displays Lasers & Sources Micro/Nano Lithography Nanotechnology Optical Design & Engineering Optoelectronics & Communications Remote Sensing Sensing & Measurement Solar & Alternative Energy Sign up for Newsroom E-Alerts Information for: Advertisers Jared Shamwell, Hyungtae Lee, Heesung Kwon, Amar R. Marathe, Vernon Lawhern and William Nothwang Preliminary results from a single-trial rapid serial visual representation task demonstrate the potential for enabling generalized human-autonomy sensor fusion across multiple subjects. 13 August 2016, SPIE Newsroom. DOI: 10.1117/2.1201607.006632 Brain–computer interfaces (BCIs) have traditionally been used to enable communication and control for paralyzed patients.1 However, it is also thought that BCIs hold promise for fulfilling the longstanding goal of creating artificial systems (i.e., which can perform with the adaptability,…
Link to Full Article: A novel convolutional neural network for deep-learning classification
A novel convolutional neural network for deep-learning classification
