Artificial neural network weights penalization and initialization for spectroscopic data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F21%3APU142523" target="_blank" >RIV/00216305:26620/21:PU142523 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Artificial neural network weights penalization and initialization for spectroscopic data
Original language description
Nowadays, Artificial Neural Networks (ANNs) are among the most utilized techniques for the advanced processing of spectroscopic data. However, several problems have emerged from such a broad adoption that are limiting their performance and trustworthiness. The most significant shortcomings are: 1) “blackbox-like” utilization of ANNs, 2) overtrained and overparametrized models, and 3) a direct transition of ANN architecture from different tasks and data types (e.g. image processing). In this work, we mainly focus on the third mentioned problem and propose several adjustments to the architecture and learning process of ANNs, which are suitable for spectroscopic data. Our approach is based on the unique properties of spectroscopic data and their direct exploitation in form of special weight initialization strategies or penalizations of the loss function. Adjusted models provide improved analytical performance and interpretability.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF19_073%2F0016948" target="_blank" >EF19_073/0016948: Quality internal grants at BUT</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů