Latent Space Exploration of Neural Networks for Annotation Efficient Subsurface Interpretation and Characterization

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Event Details
  • Date/Time:
    • Friday April 15, 2022
      9:00 am - 11:00 am
  • Location: https://gatech.zoom.us/j/94197195720
  • Phone:
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  • Fee(s):
    N/A
  • Extras:
Contact
No contact information submitted.
Summaries

Summary Sentence: Latent Space Exploration of Neural Networks for Annotation Efficient Subsurface Interpretation and Characterization

Full Summary: No summary paragraph submitted.

Title:  Latent Space Exploration of Neural Networks for Annotation Efficient Subsurface Interpretation and Characterization

Committee: 

Dr. AlRegib, Advisor    

Dr. Anderson, Chair

Dr. Davenport

Abstract: The objective of the proposed research is to explore the use of deep autoencoders and learn data manifolds to rank and characterize unlabeled training examples by their outof-distribution-score. It is theorized that this ranking can be used to select and annotate only the most informative training samples for seismic interpretation tasks, greatly reducing the annotation effort for seismic interpreters.

Additional Information

In Campus Calendar
No
Groups

ECE Ph.D. Proposal Oral Exams

Invited Audience
Public
Categories
Other/Miscellaneous
Keywords
Phd proposal, graduate students
Status
  • Created By: Daniela Staiculescu
  • Workflow Status: Published
  • Created On: Apr 9, 2022 - 9:42am
  • Last Updated: Apr 9, 2022 - 9:42am