首页|Lublin University of Technology Reports Findings in Machine Learning (Ultrasound tomography enhancement by signal feature extraction with modular machine learning method)
Lublin University of Technology Reports Findings in Machine Learning (Ultrasound tomography enhancement by signal feature extraction with modular machine learning method)
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NETL
NSTL
Public Library Science
New research on Machine Learning is the subject of a report. According to news reporting out of Lublin, Poland, by NewsRx editors, research stated, “Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography.” Our news journalists obtained a quote from the research from the Lublin University of Technology, “The key idea is to analyze the time-dependent ultrasonic signal recorded by three independent transducers of an experimental system. It focuses on finding common or related characteristics of these signals using customdesigned deep neural network models. In principle, models use convolution layers to extract common features of signals, which are passed to dense layers responsible for predicting the number of objects or their locations and sizes. Predicting the number and properties of objects are characterized by a high value of the coefficient of determination R2 = 99.8% and R2 = 98.4%, respectively.”
NETL
NSTL
Public Library Science
