首页|Researchers from University of Shanghai for Science and Technology Report Findin gs in Intelligent Systems (An End-to-end Hand Action Recognition Framework Based On Cross-time Mechanomyography Signals)
Researchers from University of Shanghai for Science and Technology Report Findin gs in Intelligent Systems (An End-to-end Hand Action Recognition Framework Based On Cross-time Mechanomyography Signals)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning - Intelligent Systems are discussed in a newreport. According to news originati ng from Shanghai, People’s Republic of China, by NewsRx correspondents,research stated, “The susceptibility of mechanomyography (MMG) signals acquisition to se nsordonning and doffing, and the apparent time-varying characteristics of biome dical signals collected overdifferent periods, inevitably lead to a reduction i n model recognition accuracy. To investigate the adverseeffects on the recognit ion results of hand actions, a 12-day cross-time MMG data collection experimentwith eight subjects was conducted by an armband, then a novel MMG-based hand act ion recognitionframework with densely connected convolutional networks (DenseNe t) was proposed.”
ShanghaiPeople’s Republic of ChinaAs iaIntelligent SystemsMachine LearningUniversity of Shanghai for Science an d Technology
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