Deep Learning for Connectomicss

author: Shuiwang Ji, School of Electrical Engineering and Computer Science, Washington State University
published: Oct. 25, 2016,   recorded: August 2016,   views: 1240
Categories

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

The importance of research that aims to unlock the mystery of the human brain has recently been recognized worldwide. In January 2013, the European Union selected the Human Brain Project to be one of its two flagship projects. In April 2013, the White House announced the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to generate a dynamic map of the brain. As these projects move forward, big data analytics will be playing increasingly important roles in converting big brain data into useful knowledge. A key challenge in analyzing brain data is to construct feature representations from brain images. In this talk, I will discuss our efforts in developing deep computational models for learning representations from brain data. In particular, I will provide details on how to use deep learning methods to elucidate the micro-scale brain connectomics among neurons. I will also show that our methods can be used in a number of diverse computational brain discovery tasks. Additionally, they may be used in other areas beyond brain analytics.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: