Described is a system that can recognize novel objects that the system has never before seen. The system uses a training image set to learn a model that maps visual features from known images to semantic attributes. The learned model is used to map visual features of an unseen input image to semantic attributes. The unseen input image is classified as belonging to an image class with a class label. A device is controlled based on the class label.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    ZERO SHOT MACHINE VISION SYSTEM VIA JOINT SPARSE REPRESENTATIONS


    Weitere Titelangaben:

    ZERO-SHOT-MASCHINENSICHTSYSTEM ÜBER GEMEINSAME SPARSE-REPRESENTATION
    SYSTÈME DE VISION DE MACHINE SANS DONNÉE DE RÉFÉRENCE PAR L'INTERMÉDIAIRE DE REPRÉSENTATIONS ÉPARSES COMMUNES


    Beteiligte:
    KOLOURI SOHEIL (Autor:in) / RAO SHANKAR R (Autor:in) / KIM KYUNGNAM (Autor:in)

    Erscheinungsdatum :

    20.01.2021


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60R Fahrzeuge, Fahrzeugausstattung oder Fahrzeugteile, soweit nicht anderweitig vorgesehen , VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR / G06K Erkennen von Daten , RECOGNITION OF DATA



    ZERO SHOT MACHINE VISION SYSTEM VIA JOINT SPARSE REPRESENTATIONS

    KOLOURI SOHEIL / RAO SHANKAR / KIM KYUNGNAM | Europäisches Patentamt | 2019

    Freier Zugriff

    Zero shot machine vision system via joint sparse representations

    KOLOURI SOHEIL / RAO SHANKAR R / KIM KYUNGNAM | Europäisches Patentamt | 2020

    Freier Zugriff

    Sparse Representations for Medium Level Vision

    Forssen, P.-E. | British Library Online Contents | 2002



    Sparse Representations for Image Decompositions

    Geiger, D. / Liu, T.-L. / Donahue, M. J. | British Library Online Contents | 1999