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High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry 、 texture and attribute characteristic. The pixel-based image classification can’t satisfy high-resolution satellite image’s classification precision and produce large data redundancy. Object-oriented(More)
Ontology is the branch of metaphysics that deals with the nature of being. Ontology is currently used by philosophers, information scientists and psychologists. A sharing ontology is required for communicating between the communicating participants. And the formal description of ontology is fundamental to data exchange standards. In recent years, ontology(More)
Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and(More)
Mobile health (mHealth), as an important development direction of eHealth, is an innovative application of spatial information technology used in health field. In this paper, the key technology of location based mobile health system is studied and the system prototype is designed and implemented. The mobile monitoring terminal receives data collected by the(More)
One novel composite kernel based support vector machine (SVM), which is called DOCKSVM (Data Oriented Composite Kernel based Support Vector Machine) is proposed in the paper. SVM have been proved good potential in various studies, and tried to application for pattern classification problems such as text categorization, image classification, objects(More)
This paper describes the development of a 1-km landcover dataset of China by using monthly NDVI data spanning April 1992 through March 1993. The method used combined unsupervised and supervised classification of NDVI data from Ž . AVHRR. It is composed of five steps: a unsupervised clustering of monthly AVHRR NDVI maximum value composites is Ž . performed(More)