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Computer Vision for Side Scan Sonar by j.hatami is a document available to read on EtoBox.

What is Computer Vision for Side Scan Sonar about?

The paper reviews current deep learning methods for automatic image classification, object detection, semantic segmentation, and instance segmentation in side-scan sonar (SSS) imagery. It discusses the challenges in underwater target detection, highlights gaps in existing research, and proposes the creation of standardized benchmarks for evaluation. The study also provides an inventory of publicly available SSS datasets and emphasizes the importance of evaluation metrics in assessing model performance.

Author

j.hatami

Language

EN