Non-stationary neural signal to image conversion framework for image-based deep learning algorithms

HIGHLIGHTS

  • who: Sahaj Anilbhai Patel from the National Institute of Technology, India King Abdulaziz University, Saudi Arabia have published the article: Non-stationary neural signal to image conversion framework for image-based deep learning algorithms, in the Journal: (JOURNAL)
  • how: This paper presents a robust preprocessing approach to classify neural spikes in 2D CNN by converting 1D non-stationary neural recording into a 2D image representation.

SUMMARY

    In the preprocessing feature extraction or representation step, most researchers employed different Frequency and TimeFrequency (TF) domain methods that convert 1D non-stationary signals into . . .

     

    Logo ScioWire Beta black

    If you want to have access to all the content you need to log in!

    Thanks :)

    If you don't have an account, you can create one here.

     

Scroll to Top

Add A Knowledge Base Question !

+ = Verify Human or Spambot ?