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    Deep Learning based Vehicle Detection in Aerial Imagery

    Dissertations in Series (Dissertationen in Schriftenreihe)

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    Author(s)
    Wilko Sommer, Lars
    Collection
    AG Universitätsverlage
    Language
    English
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    Abstract
    This book proposes a novel deep learning based detection method, focusing on vehicle detection in aerial imagery recorded in top view. The base detection framework is extended by two novel components to improve the detection accuracy by enhancing the contextual and semantical content of the employed feature representation. To reduce the inference time, a lightweight CNN architecture is proposed as base architecture and a novel module that restricts the search area is introduced.
    URI
    https://library.oapen.org/handle/20.500.12657/53149
    Keywords
    Objektdetektion; Neuronale Netze; Luftbilddaten; Object Detection; Deep Learning; Aerial Imagery
    DOI
    10.5445/KSP/1000135415
    ISBN
    9783731511137, 9783731511137
    Publisher
    KIT Scientific Publishing
    Publisher website
    https://www.ksp.kit.edu/index.php?link=shop&sort=all
    Publication date and place
    Karlsruhe, 2022
    Imprint
    KIT Scientific Publishing
    Series
    Karlsruher Schriften zur Anthropomatik, 52
    Classification
    Maths for computer scientists
    Pages
    276
    Rights
    http://creativecommons.org/licenses/by-sa/4.0
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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