{
    "o:id": 13056,
    "url": "https://chloe.cnr.it/s/BiDiAr/item/13056",
    "o:resource_template": "Academic Article",
    "o:resource_class": "bibo:AcademicArticle",
    "dcterms:title": [
        "Mapping Archeological Signs From Airborne Lidar Data Using Deep Neural Networks: Primary Results"
    ],
    "dcterms:creator": [
        "Küçükdemirci, Melda",
        "Landeschi, Giacomo",
        "Dell’Unto, Nicolo",
        "Ohlsson, Mattias"
    ],
    "dcterms:date": [
        "2021"
    ],
    "dcterms:language": [
        "eng"
    ],
    "dcterms:rights": [
        "https://creativecommons.org/licenses/by-nc-nd/4.0/"
    ],
    "dcterms:abstract": [
        "– Complexity of large-scale Airborne LIDAR data: its processing, and interpretation emerges the necessity of automated analysis with novel techniques. – Detection and documentation of archaeological ruins, hidden in the forests of the Swedish landscape."
    ],
    "dcterms:isPartOf": [
        "ArcheoSciences. Revue d'archéométrie"
    ],
    "bibo:doi": [
        "https://doi.org/10.4000/archeosciences.10179"
    ],
    "bibo:issn": [
        "1960-1360"
    ],
    "bibo:issue": [
        "45"
    ],
    "bibo:pages": [
        "291-293"
    ],
    "bibo:shortTitle": [
        "Mapping Archeological Signs From Airborne Lidar Data Using Deep Neural Networks"
    ],
    "bibo:uri": [
        "https://journals.openedition.org/archeosciences/10179"
    ],
    "foaf:homepage": [
        "https://www.zotero.org/groups/5293298/bidiar/items/28RMSD7I/item-list"
    ]
},