RADIAL BASIS NEURAL NETWORK WITH MULTIPLE CONNECTED WEIGHTS
In this work, we propose a new type of radial basis neural network model where the connection between two units is not a single value but a set of values, which means multi-connect...
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Khudaybergenov Kabul
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SKELETON-BASED HUMAN ACTION RECOGNITION USING SPATIO-TEMPORAL LATENT FEATURES WITH GCN MODEL
In this work we present LFHAR (Latent Features for Human Action Recognition), a novel architecture that utilizes multiple spatio-temporal latent representations to improve action f...