Asanobu Kitamoto

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This paper introduces the Digital Typhoon project, whose goal is to establish the study of meteoinformatics and to develop emergency information systems in the domain of typhoon-related information. We first propose the models of emergency information systems and uses " flat-source model " as the model of emergency information systems, and explain the(More)
This paper introduces the application of data mining methods to the analysis and prediction of the typhoon. The testbed for this research is the typhoon image collection that we established, now archiving approximately 34,000 typhoon images created from satellite images of geostationary meteorological satellite GMS-5. We claim that this data collection is a(More)
Weather is a typical topic of daily conversations, so it is a natural idea to use social data to observe weather. Geotagging is a key to use social data for weather applications because weather is a highly localized phenomenon on the earth. Hence we developed software called GeoNLP for toponym-based geotagging, and applied it to Twitter data stream to find(More)
Our research aims at discovering useful knowledge from the large collection of satellite images of typhoons using data mining approaches. We first introduce the creation of the typhoon image collection that consists of around 34,000 typhoon images for the northern and southern hemisphere, providing the medium-sized, richly-variational and quality-controlled(More)
The purpose of this paper is to establish an image classification method which properly considers the spatial quantisation effect of digital imagery and its inevitable consequence, the presence of mixels. To achieve this goal, we propose two new probabilistic models, namely the area proportion distribution and mixel distribution. The former probabilistic(More)