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When applied to speech, Non-negative Matrix Factorization is capable of learning a small vocabulary of words, foregoing any prior linguistic knowledge. This makes it adequate for small-scale speech applications where flexibility is of the utmost importance, e.g. assistive technology for the speech impaired. However, its performance depends on the way its inputs are represented. We propose the use...
browsing can identify an image. In text-based retrieval, images are retrieved using keywords, like subject, headings, or classification codes, which in turn are used as retrieval keys during search and retrieval of images. Usually, the only way of searching these collections of images was by keyword indexing, or simply by
Despite the tremendous importance and availability of large video collections, support for video retrieval is still rather limited and is mostly tailored to very concrete use cases and collections. In image retrieval, for instance, standard keyword search on the basis of manual annotations and content-based image
consuming, error prone and it has been shown that manual segmentations are not necessarily the optimal spatial enclosure for object classifiers. This paper proposes a weakly-supervised system for multi-label image classification. In this setting, training images are annotated with a set of keywords describing their contents
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