首页|Polytechnic University Torino Reports Findings in Machine Learning (Near-field m icrowave sensing technology enhanced with machine learning for the non-destructi ve evaluation of packaged food and beverage products)
Polytechnic University Torino Reports Findings in Machine Learning (Near-field m icrowave sensing technology enhanced with machine learning for the non-destructi ve evaluation of packaged food and beverage products)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Turin, Italy, by NewsR x editors, research stated, "In the food industry, the increasing use of automat ic processes in the production line is contributing to the higher probability of finding contaminants inside food packages. Detecting these contaminants before sending the products to market has become a critical necessity." Financial support for this research came from Franco-Italian University. Our news journalists obtained a quote from the research from Polytechnic Univers ity Torino, "This paper presents a pioneering real-time system for detecting con taminants within food and beverage products by integrating microwave (MW) sensin g technology with machine learning (ML) tools. Considering the prevalence of wat er and oil as primary components in many food and beverage items, the proposed t echnique is applied to both media. The approach involves a thorough examination of the MW sensing system, from selecting appropriate frequency bands to characte rizing the antenna in its near-field region. The process culminates in the colle ction of scattering parameters to create the datasets, followed by classificatio n using the Support Vector Machine (SVM) learning algorithm. Binary and multicla ss classifications are performed on two types of datasets, including those with complex numbers and amplitude data only."
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