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        "title": "Assessment of Material Layers in Building Walls Using GeoRadar",
        "date": "2022-10-09",
        "abstract": "Assessing the structure of a building with non-invasive methods is an important problem. One of the possible approaches is to use GeoRadar to examine wall structures by analyzing the data obtained from the scans. However, so far, the obtained data have to be assessed manually, relying on the experience of the user in interpreting GPR radargrams. We propose a data-driven approach to evaluate the material composition of a wall from its GPR radargrams. In order to generate training data, we use gprMax to model the scanning process. Using simulation data, we use a convolutional neural network to predict the thicknesses and dielectric properties of walls per layer. We evaluate the generalization abilities of the trained model on the data collected from real buildings.",
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        "doi": "10.3390/rs14195038",
        "event": "Radar Techniques for Structures Characterization and Monitoring",
        "issn": "2072-4292",
        "journal": "Remote Sensing",
        "number": "19",
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        "pages": "12",
        "pages_from": "5038",
        "publisher": "MDPI",
        "volume": "14",
        "research_areas": [
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        ],
        "keywords": [
            "deep learning",
            "ground-penetrating radar",
            "non-destructive-evaluation"
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    {
        "id": "Honic_2021",
        "type_id": "techreport",
        "tu_id": 299184,
        "repositum_id": "20.500.12708/40378",
        "title": "SCI_BIM Scanning and data capturing for Integrated Resources and Energy Assessment using Building Information Modelling",
        "date": "2021",
        "abstract": "Due to the rapidly increasing consumption of resources and land worldwide, as well as the growing generation of waste, the building stock plays a crucial role not only for the reduction of the energy \n consumption, but also as a future source of materials (urban mining). However, there is a lack of information on the detailed material composition of the building stock, which is the main obstacle for \n modelling and predicting its future use. Therefore, the main research question is whether the use of the digital technologies \"Laser Scanning\" and \"Ground Penetrating Radar\" (GPR) as well as a \n gamification concept, enable to develop and maintain a digital twin (BIM model) which serves as a basis for urban mining.",
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            1909,
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        "number": "TR-193-02-2021-2",
        "open_access": "yes",
        "pages": "62",
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    {
        "id": "honic-2020-w78",
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        "tu_id": null,
        "repositum_id": "20.500.12708/62920",
        "title": "Scan to BIM for the Semi-Automated Generation of a Material Passport for an Existing Building",
        "date": "2020-08",
        "abstract": null,
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        "booktitle": " Proceedings of the 37th International Conference of CIB W78",
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