Please use this identifier to cite or link to this item: http://archives.univ-biskra.dz/handle/123456789/24882
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dc.contributor.authorBenbraika, Souad-
dc.date.accessioned2023-05-02T09:57:16Z-
dc.date.available2023-05-02T09:57:16Z-
dc.date.issued2018-
dc.identifier.urihttp://archives.univ-biskra.dz/handle/123456789/24882-
dc.description.abstractWe propose a novel multi label (ML) classification approach based on the Conditional Random fields (CRF) for the high resolution UAV images. The inderlying idea of the proposed model integrate 1) spatial information within the same class; jointly with 2) cross-correlation information between different class labels after . The experiments were done on two different UAV image datasets and the experimental results show that the new model outperforms conventional approaches.en_US
dc.language.isoenen_US
dc.subjectConditional random fields (CRF), Markovian random fields(MRF), Image multilabeling classification, Spatial contextual information, UAV images.en_US
dc.titleConditional Field for Image Classificationen_US
dc.typeThesisen_US
Appears in Collections:Mathématiques

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