Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms

Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms

This paper focuses on reducing energy consumption in ultrasound tomography by utilizing machine learning techniques. The core idea is to investigate the feasibility of minimizing the number of measurement sensors without sacrificing prediction accuracy. This article evaluates the quality of reconstr...

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Bibliographic Details
Main Authors: Bartłomiej Baran, Tomasz Rymarczyk, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, Tomasz Cieplak, Marcin Gąsior, Marcin Marczuk, Edmund Wąsik, Konrad Gauda
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Energies
Subjects:
ultrasound tomography
machine learning
object detection
localization
energy optimization
Online Access:https://www.mdpi.com/1996-1073/17/21/5406
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