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Zero shot machine vision system via joint sparse representations
Zero shot machine vision system via joint sparse representations
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机译:通过联合稀疏表示的零镜头机器视觉系统
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摘要
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.
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