2 code implementations • 15 Nov 2023 • Vojtěch Čermák, Lukas Picek, Lukáš Adam, Kostas Papafitsoros
In this paper, we present WildlifeDatasets (https://github. com/WildlifeDatasets/wildlife-datasets) - an open-source toolkit intended primarily for ecologists and computer-vision / machine-learning researchers.
no code implementations • 9 Nov 2023 • Lukáš Adam, Vojtěch Čermák, Kostas Papafitsoros, Lukáš Picek
This paper introduces the first public large-scale, long-span dataset with sea turtle photographs captured in the wild -- SeaTurtleID2022 (https://www. kaggle. com/datasets/wildlifedatasets/seaturtleid2022).
no code implementations • 18 Nov 2022 • Lukáš Adam, Vojtěch Čermák, Kostas Papafitsoros, Lukáš Picek
This paper introduces the first public large-scale, long-span dataset with sea turtle photographs captured in the wild -- \href{https://www. kaggle. com/datasets/wildlifedatasets/seaturtleid2022}{SeaTurtleID2022}.
no code implementations • 14 Oct 2021 • Vojtěch Čermák, Lukáš Adam
Due to the projection, all iterations are feasible, and our method always generates adversarial images.
no code implementations • 22 Jun 2020 • Václav Mácha, Lukáš Adam, Václav Šmídl
Accuracy at the top is a special class of binary classification problems where the performance is evaluated only on a small number of relevant (top) samples.
2 code implementations • 26 Feb 2020 • Václav Mácha, Lukáš Adam, Václav Šmídl
Many classification problems focus on maximizing the performance only on the samples with the highest relevance instead of all samples.
no code implementations • 25 Feb 2020 • Lukáš Adam, Václav Mácha, Václav Šmídl, Tomáš Pevný
Many binary classification problems minimize misclassification above (or below) a threshold.
1 code implementation • 22 Jul 2019 • Lukáš Adam, Xin Yao
Robust optimization over time (ROOT) refers to an optimization problem where its performance is evaluated over a period of future time.