Trent University Graduate Thesis Collection

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tula:etd
Type
Collection
Language
eng
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1 item
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Copyright for all items in the Trent University Graduate Thesis Collection is held by the author, with all rights reserved, unless otherwise noted.
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Deep learning for removal of non-resonant background in CARS hyperspectroscopy

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Year: 2023, 2023
Member of: Trent University Graduate Thesis Collection
Name(s): Creator (cre): Olaniyan, George Aderopo, Thesis advisor (ths): Slepkov, Aaron D, Degree committee member (dgc): Vreugdenhil, Andrew, Degree committee member (dgc): Gaspari, Franco, Degree granting institution (dgg): Trent University
Abstract: <p>In this work, a deep learning approach proposed by Valensise et al. [3] for extracting Raman resonant spectra from measured broadband CARS spectra was explored to see how effective it is at removing NRB from our experimentally measured "spectral-focusing"-based approach to CARS. A large dataset of realistic simulated CARS spectra was used to train a model capable of performing… more
Full Text: Deep learning for removal of non-resonant background in CARS hyperspectroscopy A thesis submitted to the Committee on Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Faculty of Art and Science Trent …