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pro vyhledávání: '"Haberger, David"'
Autor:
Ausserlechner, Philipp, Haberger, David, Thalhammer, Stefan, Weibel, Jean-Baptiste, Vincze, Markus
As robotic systems increasingly encounter complex and unconstrained real-world scenarios, there is a demand to recognize diverse objects. The state-of-the-art 6D object pose estimation methods rely on object-specific training and therefore do not gen
Externí odkaz:
http://arxiv.org/abs/2309.11986
The following paper is a reproducibility report for "A Light-Weight Strategy for Restraining Gender Biases in Neural Rankers" \cite{bigdeli2022light} published in ECIR 2022. The authors, Bigdeli et al., claim that their negative sampling strategy dec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6026d02cee2882f6b2f03afcca00ecf8