agrija9/ssl-sonar-images
Code for our paper Self-supervised Learning for Sonar Image Classification [CVPR 2022]
This project helps marine robotics engineers and researchers automatically identify objects in sonar images, even when they have very few labeled examples. It takes raw sonar images as input and produces categorized classifications of objects within those images. This is particularly useful for those working with autonomous underwater vehicles (AUVs) or remotely operated vehicles (ROVs) where manual labeling of vast sonar datasets is impractical or impossible due to data sensitivity.
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Use this if you need to classify objects in sonar images but struggle with limited access to large, human-labeled datasets.
Not ideal if you already have extensive, well-labeled sonar image datasets and are familiar with standard supervised deep learning approaches.
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Jun 28, 2022
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