Titlebook: Artificial Intelligence Oceanography; Xiaofeng Li,Fan Wang Book‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicable) and The Author(s) 2023 Open Acc

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The Natural Language of Random Processes,e mean absolute errors of length and width estimated by the SSENet are 7.88 and 2.23?m, respectively. Compared to the old mean square error loss function, the new MSSE reduces the length’s MAE by approximately 1 m. SSENet demonstrates its robustness over a variety of training/testing sets.

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,Detecting Tropical Cyclogenesis Using Broad Learning System from?Satellite Passive Microwave Observd 2506 non-TC samples during 2005–2006, which are . images extracted from Special Sensor Microwave Imager TB data. The proposed model successfully detects tropical cyclogenesis with a total testing accuracy of 86.83%, a testing hit rate (HT) of 81.14%, and a testing false alarm ratio (FAR) of 11.18%.

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,Automatic Waterline Extraction of?Large-Scale Tidal Flats from?SAR Images Based on?Deep Convolutionlat’s digital elevation model (DEM) of Subei Bank automatically using the waterline method. The results indicates that our DCNN model not only has appreciable performance for extraction of waterline in SAR images under complex imaging conditions but also excellent potential for rapid analysis of tidal flat topography evolution.

MURAL

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Serenity

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