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pro vyhledávání: '"Arnez, Fabio"'
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estimating confidence in DNN predictions. Bayesian Deep Learning (BDL) offe
Externí odkaz:
http://arxiv.org/abs/2301.05297
Filming sport videos from an aerial view has always been a hard and an expensive task to achieve, especially in sports that require a wide open area for its normal development or the ones that put in danger human safety. Recently, a new solution aros
Externí odkaz:
http://arxiv.org/abs/2212.11402
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estimating confidence in DNN predictions. Bayesian Deep Learning (BDL) offe
Externí odkaz:
http://arxiv.org/abs/2206.01953
Uncertainty quantification methods are required in autonomous systems that include deep learning (DL) components to assess the confidence of their estimations. However, to successfully deploy DL components in safety-critical autonomous systems, they
Externí odkaz:
http://arxiv.org/abs/2110.13729
A key factor for ensuring safety in Autonomous Vehicles (AVs) is to avoid any abnormal behaviors under undesirable and unpredicted circumstances. As AVs increasingly rely on Deep Neural Networks (DNNs) to perform safety-critical tasks, different meth
Externí odkaz:
http://arxiv.org/abs/2006.15172
Publikováno v:
2022 18th European Dependable Computing Conference (EDCC).
As autonomous systems increasingly rely on Deep Neural Networks (DNN) to implement the navigation pipeline functions, uncertainty estimation methods have become paramount for estimating confidence in DNN predictions. Bayesian Deep Learning (BDL) offe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b52ac994c76543c3413fadfe0cfc426
https://doi.org/10.1109/edcc57035.2022.00021
https://doi.org/10.1109/edcc57035.2022.00021
Autor:
Arnéz, Fábio Alcoba
Publikováno v:
Biblioteca Digital de Teses e Dissertações da UFRGSUniversidade Federal do Rio Grande do SulUFRGS.
Este trabalho apresenta o desenvolvimento de uma metodologia para a avaliação de critérios de outorga do uso da água na bacia do rio Santa Maria. A escolha da bacia do rio Santa Maria se deve ao fato da existência de conflitos pelo uso da água,
Externí odkaz:
http://hdl.handle.net/10183/1577