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Communication dans un congrès
Ultimate levelings with strategy for filtering undesirable residues based on machine learning
Abstract : Ultimate levelings are operators that extract important image contrast information from a scale-space based on levelings. During the residual extraction process, it is very common that some residues are selected from undesirable regions, but they should be filtered out. In order to avoid this problem some strategies can be used to filter residues extracted by ultimate levelings. In this paper, we introduce a novel strategy to filter undesirable residues from ultimate levelings based on a regression model that predicts the correspondence between objects of interest and residual regions. In order to evaluate our new approach, some experiments were carried out with a plant dataset and the results show the robustness of our method.
Littérature citée [25 références]
https://hal-mines-paristech.archives-ouvertes.fr/hal-02430523
Contributeur : Beatriz Marcotegui <>
Soumis le : mardi 7 janvier 2020 - 13:21:23
Dernière modification le : jeudi 24 septembre 2020 - 16:38:04
Contributeur : Beatriz Marcotegui <>
Soumis le : mardi 7 janvier 2020 - 13:21:23
Dernière modification le : jeudi 24 septembre 2020 - 16:38:04
Fichier
2019_ismm_UL_ML_wonder.pdf
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