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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

  • DOI - Digital Object Identifier

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

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

  • 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