首页|New Findings in Machine Learning Described from Swiss Federal Institute of Techn ology (A Cloud-native Approach for Processing of Crowdsourced Gnss Observations and Machine Learning At Scale: a Case Study From the Camaliot Project)
New Findings in Machine Learning Described from Swiss Federal Institute of Techn ology (A Cloud-native Approach for Processing of Crowdsourced Gnss Observations and Machine Learning At Scale: a Case Study From the Camaliot Project)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating in Zurich, Switzerland, by NewsRx journalists, research stated, “The era of modern smartphones, running on Android version 7.0 and higher, facilitates nowadays acquisition of raw dual -frequency multiconstellation GNSS observations. This paves the way for GNSS co mmunity data to be potentially exploited for precise positioning, GNSS reflectom etry or geoscience applications at large.”
ZurichSwitzerlandEuropeCyborgsEm erging TechnologiesMachine LearningSwiss Federal Institute of Technology
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