首页|New Findings on Machine Learning Described by Investigators at Sao Paulo State University (UNESP) (Unsupervised Change Detection Methods Applied To Landslide Ma pping: Case Study In Sao Sebastiao, Brazil)
New Findings on Machine Learning Described by Investigators at Sao Paulo State University (UNESP) (Unsupervised Change Detection Methods Applied To Landslide Ma pping: Case Study In Sao Sebastiao, Brazil)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news originating from Sao Jose dos Campos, Brazil, by NewsRx correspondents, research stated, “Landslides represent a growing glo bal geological hazard, further intensified by climate-induced changes. Remote se nsing data, through its capacity for repetitive collection and change detection techniques, that compare and quantify the spatio-temporal alterations over time, plays a critical role in landslide detection.”
Sao Jose dos CamposBrazilSouth AmericaCyborgsEmerging TechnologiesMachine LearningSao Paulo State University (UNESP)
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