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.
ZERO SHOT MACHINE VISION SYSTEM VIA JOINT SPARSE REPRESENTATIONS
ZERO-SHOT-MASCHINENSICHTSYSTEM ÜBER GEMEINSAME SPARSE-REPRESENTATION
SYSTÈME DE VISION DE MACHINE SANS DONNÉE DE RÉFÉRENCE PAR L'INTERMÉDIAIRE DE REPRÉSENTATIONS ÉPARSES COMMUNES
2021-01-20
Patent
Electronic Resource
English
IPC: | G06K Erkennen von Daten , RECOGNITION OF DATA / B60R Fahrzeuge, Fahrzeugausstattung oder Fahrzeugteile, soweit nicht anderweitig vorgesehen , VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen |
ZERO SHOT MACHINE VISION SYSTEM VIA JOINT SPARSE REPRESENTATIONS
European Patent Office | 2019
|Zero shot machine vision system via joint sparse representations
European Patent Office | 2020
|Sparse Representations for Medium Level Vision
British Library Online Contents | 2002
|Sparse Representations for Image Decompositions
British Library Online Contents | 1999
|