Search Results - "Boudra, Safia"

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  1. 1

    A set of statistical radial binary patterns for tree species identification based on bark images by Boudra, Safia, Yahiaoui, Itheri, Behloul, Ali

    Published in Multimedia tools and applications (01-06-2021)
    “…This paper deals with bark texture representation at high scale-space levels for tree species identification. The proposed approach, named, a set of…”
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    Journal Article
  2. 2

    Tree trunk texture classification using multi-scale statistical macro binary patterns and CNN by Boudra, Safia, Yahiaoui, Itheri, Behloul, Ali

    Published in Applied soft computing (01-03-2022)
    “…Automated plant classification using tree trunk has attracted increasing interest in the computer vision community as a contributed solution for the management…”
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    Journal Article
  3. 3

    Pseudonym Limitation for Privacy in Cooperative Transport Systems by Fouchal, Hacene, Boudra, Safia, Ercan, Secil, Yahiaoui, Itheri

    Published in IEEE network (01-05-2020)
    “…C-ITS is one of the most challenging domains in either research or industry. Their social and economic benefits are of importance for fuel consumption, traffic…”
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    Journal Article
  4. 4

    Plant identification from bark: A texture description based on Statistical Macro Binary Pattern by Boudra, Safia, Yahiaoui, Itheri, Behloul, Ali

    “…This paper presents a novel, yet compact texture descriptor for plant species identification based on bark texture images. Termed Statistical Macro Binary…”
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    Conference Proceeding
  5. 5

    FPDM: Fisheye Panoptic segmentation dataset for Door Monitoring by Thioune, Mohamed, Chafik, Sanaa, Mahtani, Ankur, Laurendin, Olivier, Boudra, Safia

    “…Most existing panoptic segmentation datasets are not suited for applications in the railway environment. This paper introduces a new dataset composed of video…”
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    Conference Proceeding
  6. 6

    Bark Identification Using Improved Statistical Radial Binary Patterns by Boudra, Safia, Yahiaoui, Itheri, Behloul, Ali

    “…In this paper, we explore the texture representation at high scale levels for the application of tree bark identification. We mainly propose an Improved…”
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    Conference Proceeding