Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session M34: Photodetectors and Optical Emitters
8:00 AM–10:48 AM,
Wednesday, March 8, 2023
Room: Room 226/227
Sponsoring
Unit:
FIAP
Chair: Jay Mathews, University of Dayton
Abstract: M34.00002 : Raman spectroscopy in open world learning settings using the Objectosphere approach*
8:12 AM–8:24 AM
Presenter:
Yaroslav Balytskyi
(University of Colorado Colorado Springs)
Author:
Yaroslav Balytskyi
(University of Colorado Colorado Springs)
To overcome these barriers, we implemented the recently introduced Entropic Open Set and Objectosphere loss functions. To demonstrate the efficacy and efficiency of this approach, we compiled a database of hyperspectral Raman images of 40 chemical species separating them into 3 class categorizations. The known class consisted of 20 biologically relevant species comprised of amino acids, the ignored class was 10 ``irrelevant" species comprised of bio-related chemicals, and the never seen before class was 10 various chemical species that the Neural Network had not seen before. We show that not only does this approach enable the network to effectively separate the unknown species while preserving high accuracy on the known ones and reducing false positives, but also that it performs better than the current gold standards in machine learning techniques. This opens the door to using Raman spectroscopy, combined with our novel machine learning algorithm, in a variety of practical applications.
Availability and implementation: Freely available on the web at: https://github.com/BalytskyiJaroslaw/RamanOpenSet.git.
*This work was supported by:1) National Institute of General Medical Sciences of the National Institutes of Health [grant number 1R15GM128166–01]2) UCCS BioFrontiers Center3) U.S. Civilian Research & Development Foundation (CRDF Global)
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