首页|Data on Machine Learning Reported by Researchers at School of Resources & Safety Engineering (Classification of Arsenic Contamination In Soil Across the E u By Vis-nir Spectroscopy and Machine Learning)
Data on Machine Learning Reported by Researchers at School of Resources & Safety Engineering (Classification of Arsenic Contamination In Soil Across the E u By Vis-nir Spectroscopy and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting originating from Changsha, P eople’s Republic of China, by NewsRx correspondents, research stated, “Detecting soil arsenic (As) contamination is crucial for designing efficient soil remedia tion strategies; however, traditional laboratory-based As detection techniques a re time- and labour-intensive and are unsuitable for large-scale spatial analyse s. To address this issue, we combined machine learning (ML) with visible-near-in frared (vis-NIR) spectroscopy to develop an efficient framework for As detection in soil.”
ChangshaPeople’s Republic of ChinaAs iaArsenicCyborgsEmerging TechnologiesMachine LearningSchool of Resourc es & Safety Engineering
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