首页|Findings from Northeastern University Reveals New Findings on Intelligent Systems (Gait Recognition Based On Multi-feature Representation and Temporal Modeling of Periodic Parts)
Findings from Northeastern University Reveals New Findings on Intelligent Systems (Gait Recognition Based On Multi-feature Representation and Temporal Modeling of Periodic Parts)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Machine Learning - Intelligent Systems. According to news originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated,“Despite the ability of 3D convolutional methods to extract spatio-temporal information simultaneously,they also increase parameter redundancy and computational and storage costs. Previous work that hasutilized the 2D convolution method has approached the problem in one of two ways: either using theentire body sequence as input to extract global features or dividing the body sequence into several partsto extract local features.”
ShenyangPeople’s Republic of ChinaAsiaIntelligent SystemsMachine LearningNortheastern University
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