首页|Findings from Federal University of Mato Grosso do Sul (UFMS) Yields New Findings on Machine Learning (Machine Learning In the Classification of Asian Rust Severity In Soybean Using Hyperspectral Sensor)
Findings from Federal University of Mato Grosso do Sul (UFMS) Yields New Findings on Machine Learning (Machine Learning In the Classification of Asian Rust Severity In Soybean Using Hyperspectral Sensor)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Machine Learning are presented in a new report. According to news reporting out of Chapadao do Sul, Brazil, by News Rx editors, research stated, “Traditional monitoring of asian soybean rust severity is a time- and labor-intensive task, as it requires visual assessments by skilled professionals in the field. Thus, the use of remote sensing and machine learning (ML) techniques in data processing has emerged as an approach that can in crease efficiency in disease monitoring, enabling faster, more accurate and time - and labor-saving evaluations.”
Chapadao do SulBrazilSouth AmericaAlgorithmsAsiaCyborgsEmerging TechnologiesMachine LearningFederal Univ ersity of Mato Grosso do Sul (UFMS)
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