Deep Learning for Deep Water: Robust classification of ship wakes with expert in the loop
Abstract: This work examines the applicability of the deep learning models to pattern recognitionin acoustic ocean data. The features of the dataset include noise, data scarcityand the lack of labeled samples. A deep learning model is proposed for the task ofautomatic wake detection. It takes advantage of the availability of an expert in themarine science domain while using data generation and robustness techniques to enhanceperformance. The model shows encouraging results, although its performance decreases with heavily unbalanced data and the introduction of noise.
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