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- W3166151471 abstract "Ship detection from satellite images is more important for the security of oceanic areas, identification of illegal oil spills, monitoring maritime traffic in the fisheries and the commercial transportation sector. However the earlier techniques for ship detection has drawbacks such as it is difficult to track the ship under worst weather conditions, clouds, high ocean waves and mist. In this paper, the ship detection from satellite images is analyzed with different scaling and illumination condition using compressed domain and wavelet domain with support vector machine (SVM) provides an efficient way to detect the ship. Furthermore, the SVM classifier used in this method offers an accurate result in the detection of the ship. Experiment shows that proposed algorithm achieves high probability of correct detection as well as the time consumption for detecting the ship is less (processing time)." @default.
- W3166151471 created "2021-06-22" @default.
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- W3166151471 date "2016-01-05" @default.
- W3166151471 modified "2023-09-25" @default.
- W3166151471 title "Ship Detection from Satellite Images Using Support Vector Machine" @default.
- W3166151471 hasPublicationYear "2016" @default.
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