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2024 | OriginalPaper | Chapter

Comparison Between Gradient Descent and Adam Algorithms for Image Reconstruction in Diffuse Optical Tomography

Authors : Nada Chakhim, Mohamed Louzar, Abdellah Lamnii, Mohammed Alaoui

Published in: Applied Mathematics and Modelling in Finance, Marketing and Economics

Publisher: Springer Nature Switzerland

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Abstract

In this work, we aim to solve the inverse problem of diffuse optical tomography by using enhanced gradient descent methods. The light propagation throughout the medium is described by the diffusion approximation in frequency domain. For comparison purpose we use the gradient descent method. We have studied the convergence of the objective functional. Our simulation results, in all cases we have tested, show the robustness and the quick convergence of Adam algorithm compared to the gradient descent algorithm.

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Metadata
Title
Comparison Between Gradient Descent and Adam Algorithms for Image Reconstruction in Diffuse Optical Tomography
Authors
Nada Chakhim
Mohamed Louzar
Abdellah Lamnii
Mohammed Alaoui
Copyright Year
2024
DOI
https://doi.org/10.1007/978-3-031-42847-0_13

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