Closing the Simulation-to-Reality Gap using Generative Neural Networks: Training Object Detectors for Soccer Robotics in Simulation as a Case Study

dc.creatorCruz N., Ruiz-Del-Solar J.
dc.date.accessioned2022-12-27T15:47:26Z
dc.date.accessioned2023-05-19T04:51:05Z
dc.date.available2022-12-27T15:47:26Z
dc.date.available2023-05-19T04:51:05Z
dc.date.created2022-12-27T15:47:26Z
dc.date.issued2020
dc.identifier10.1109/IJCNN48605.2020.9207173
dc.identifierhttps://repositorio.uchile.cl/handle/2250/191082
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6299113
dc.languageen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile
dc.sourceProceedings of the International Joint Conference on Neural Networks
dc.titleClosing the Simulation-to-Reality Gap using Generative Neural Networks: Training Object Detectors for Soccer Robotics in Simulation as a Case Study
dc.typeArtículo de revista


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