首页|New Findings from Kazan State Power Engineering University in the Area of Machin e Learning Published (Problems of Surface Defectoscopy of Metals Using Machine L earning And Ways For Their Solutions)
New Findings from Kazan State Power Engineering University in the Area of Machin e Learning Published (Problems of Surface Defectoscopy of Metals Using Machine L earning And Ways For Their Solutions)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New study results on artificial intell igence have been published. According to news reporting out of Kazan State Power Engineering University by NewsRx editors, research stated, "Rejection of metal products is an important stage of the production process aimed at ensuring the b est quality of the final product."Our news editors obtained a quote from the research from Kazan State Power Engin eering University: "Traditional rejection methods, based on visual inspection or the use of simple automated systems, have their limitations and disadvantages, such as low speed and accuracy of defect classification. The paper examines the possibility of using various machine learning methods to classify defects in met al products."According to the news editors, the research concluded: "A comparative analysis o f these algorithms, as well as their effectiveness, is carried out in order to d etermine the most suitable approach to the automatic rejection of metal products ."
Kazan State Power Engineering UniversityCyborgsEmerging TechnologiesMachine Learning
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