Sonar image automatic target identification method based on neural network visualization

Abstract

The invention discloses a sonar image automatic target identification method based on neural network visualization. By implementing the method for positioning and identifying the sonar image target only depending on the sample category labels, the labor cost of the method and the generalization ability in the field of sonar images are greatly reduced. In order to solve the problem of obvious overfitting of a training model caused by lack of a sonar data set, an optical data set used for original pre-training is converted into an optical data set based on shape preference through an adaptive instance regularization (AdaIN) style conversion method, so that the obtained pre-training parameters are more robust to shape features. Therefore, the auxiliary model focuses on extraction of specific shape features of a sonar image target in training of a sonar data set. Experiments prove that the method not only helps to solve the problem of model positioning misalignment caused by insufficient sonar data sets, but also further improves the effect of the model in the automatic target recognition task of the sonar image.

Description

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AI Technical Summary

Problems solved by technology

Most methods complete the automatic target recognition task in two steps through different techn

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