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AUTOMATED DETECTION OF EARLY TROPICAL CYCLONES FORMATION IN SATELLITE IMAGES

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dc.contributor.author I.S. Bajwa
dc.contributor.author M.N. Asghar
dc.contributor.author M.A. Naeem
dc.date.accessioned 2023-03-14T05:56:29Z
dc.date.available 2023-03-14T05:56:29Z
dc.date.issued 2017-12-14
dc.identifier.citation Bajwa, I. S. (2017). Automated detection of early tropical cyclones formation in satellite images. Pakistan Journal of Science, 69(4). en_US
dc.identifier.issn 0030-9877
dc.identifier.uri http://142.54.178.187:9060/xmlui/handle/123456789/19033
dc.description.abstract The satellite imagery based weather predictions especially identification and classification of pressure zones that leads to formation of tropical cyclones was the objective of this paper. The presented approach was based on Principal Component Analysis (PCA) algorithm and Markov Logic Networks (MLN) for identification of pressure zones where PCA was used to extract features and Markov Logic for classification purposes. The system worked in two phases: Firstly, National Oceanic and Atmospheric Administration (NOAA) satellite images which were used to train the system and in training phase, an image space was generated on the basis of the spatial features of the input images. The results of the experiments showed that Markov Logic improved the accuracy of low level clouds by 8% and for high level clouds 12% classification of pressure zones in NOAA satellite images. en_US
dc.language.iso en en_US
dc.publisher Lahore: Pakistan Association for the Advancement of Science en_US
dc.subject Image Classification en_US
dc.subject Principal Component Analysis, en_US
dc.subject Markov Logic en_US
dc.subject Satellite Images en_US
dc.subject Tropical Cyclones. en_US
dc.title AUTOMATED DETECTION OF EARLY TROPICAL CYCLONES FORMATION IN SATELLITE IMAGES en_US
dc.type Article en_US


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