Imbalanced Underwater Acoustic Target Recognition with Trigonometric Loss and Attention Mechanism Convolutional Network

Imbalanced Underwater Acoustic Target Recognition with Trigonometric Loss and Attention Mechanism Convolutional Network

A balanced dataset is generally beneficial to underwater acoustic target recognition. However, the imbalanced class distribution is always meted out in a real scene. To address this, a weighted cross entropy loss function based on trigonometric function is proposed. Then, the proposed loss function...

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Bibliographic Details
Main Authors: Yanxin Ma, Mengqi Liu, Yi Zhang, Bingbing Zhang, Ke Xu, Bo Zou, Zhijian Huang
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Remote Sensing
Subjects:
underwater acoustic target recognition
imbalanced data
trigonometric loss
deep learning
attention mechanism
Online Access:https://www.mdpi.com/2072-4292/14/16/4103

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