In order to study the recognition methods of underwater targets in harsh environments and improve the accuracy of image based underwater target recognition, a deep learning based underwater target recognition method in harsh environments was carried out. Propose a simulation method for underwater target harsh environment images based on clearer image samples. The simulation processing mainly includes adding random scale and spatial position obstructions, adding random noise, and obtaining simulated image data. Establish an integrated image dataset, which includes clearer original image data and simulated image data. The recognition results of target recognition models trained on the integrated image dataset have significantly improved compared to the original image dataset.
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