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{
    "pk": 26768,
    "title": "Multimodal Object Recognition and Categorisation by Interactive Behaviours",
    "subtitle": null,
    "abstract": "Human beings have an excellent ability which can form and recognise object categories. In this paper, a novel systemof multimodal object recognition and categorisation by perform- ing interactive behaviours is introduced. Video clips are filmedas the raw input of the system. A dataset of 100 objects with 18 categories and 5 different interactions is used to evaluated theperformance. Convolutional neural network is used to train the classifier and learn the categories. The result shows the high-est, lowest and average recognition accuracies of every specific object in every category and the receiver operating character-istic for every category. The connection between the presented system and human cognitive system is discussed in the conclu-sion and future works.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Member Abstracts",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/6479h9fw",
    "frozenauthors": [
        {
            "first_name": "Haojun",
            "middle_name": "",
            "last_name": "Guan",
            "name_suffix": "",
            "institution": "University of Hamburg",
            "department": ""
        },
        {
            "first_name": "Jianwei",
            "middle_name": "",
            "last_name": "Zhang",
            "name_suffix": "",
            "institution": "University of Hamburg",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2016-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26768/galley/16404/download/"
        }
    ]
}