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issued to the databases also contain spatial and textual components, for example, "Find shelters with emergency medical facilities in Orange County," or "Find earthquake-prone zones in Southern California." We refer to such queries as spatial-keyword queries or SK queries for short. In recent times, a lot of interest has
With large databases of document images available,a method for users to find keywords in documents will be useful. One approach is to perform Optical Character Recognition (OCR) on each document followed by indexing of the resulting text. However, if the quality of the document is poor or time is critical,complete OCR
This paper describes face image retrieval and annotation based on latent semantic indexing in FIARS. Two latent semantic spaces are constructed from visual and symbolic features to develop these mechanisms. These features are corresponding to lengths of some places of a face and its parts, and keywords, respectively
virtual universities. Vocabulary tree is an efficient search data structure based on visual-keywords. Using vocabulary tree structure can improve the retrieval efficiency, and can meet the large-scale image database demand from the adaptability and scalability requirements, thus realizes the highly effective achieve virtual
Traditional image classification techniques are based on the analysis of low-level visual features or on textual information. In this paper, we describe a novel solution which tries to improve image analysis and processing algorithms by incorporating keywords and textual annotation produced by humans in a folksonomy
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