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ACM International Conference Proceeding Series(1)
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Natural object manipulation using anthropomorphic robotic hand through deep reinforcement learning and deep grasping probability network
ArticleAbstract: Human hands can perform complex manipulation of various objects. It is beneficial if anthropomorphicPalabras claves:Anthropomorphic robotic hand, Deep grasping probability network, Deep reinforcement learning, Human grasping hand poses, Natural object grasping and relocation, Natural policy gradientAutores:Al-Antari M.A., Edwin Valarezo Anazco, Kim T.S., Oh J., Park N., Rivera Lopez P., Ryu G.Fuentes:googlescopusHuman activities recognition with a single writs imu via a variational autoencoder and android deep recurrent neural nets
ArticleAbstract: Human Activity Recognition (HAR) is an active research field because of its versatility towards variPalabras claves:Android Deep Recurrent Neural Networks, Denoising Autoencoder, Human activity recognition, Mobile applicationAutores:Edwin Valarezo Anazco, Kim T.S., Park H., Park N., Rivera P.Fuentes:googlescopusHuman-like Object Grasping and Relocation for an Anthropomorphic Robotic Hand with Natural Hand Pose Priors in Deep Reinforcement Learning
Conference ObjectAbstract: Anthropomorphic manipulators such as robotic hands (i.e., agent) can be used to perform complex objePalabras claves:Anthropomorphic Hand Manipulation, Deep Reinforcement Learning., Human-Like Object Grasping, Natural Hand Pose PriorAutores:Byun K., Edwin Valarezo Anazco, Kim T.S., Lee S., Oh J., Park H., Park N., Rivera P.Fuentes:googlescopus