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New open dataset OSSDD released for Sentinel-1 ship detection

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced OSSDD, a new open dataset designed for training neural networks to detect ships in Synthetic Aperture Radar (SAR) images. This dataset, built upon the OpenSARShip 1.0 dataset, provides 15,197 Sentinel-1 amplitude patches with detailed annotations for over 55,000 ships. OSSDD includes binary ship masks, axis-aligned bounding boxes, and rotated bounding boxes, aiming to serve as a benchmark for future SAR ship detection experiments. The dataset is accessible on Hugging Face. AI

IMPACT Provides a new benchmark dataset to advance research in SAR ship detection using neural networks.

RANK_REASON The item describes a new open dataset for a specific computer vision task, including details about its contents and experimental results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New open dataset OSSDD released for Sentinel-1 ship detection

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The item describes a new open dataset for a specific computer vision task, including details about its contents and experimental results. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Horst Hammer, Sylvia Hochstuhl, Antje Thiele, Tobias Brosch, Padraig Davidson, Tim Remiger, Michael Teutsch ·

    OSSDD - a New Open Dataset for Sentinel-1 Ship Detection

    arXiv:2608.01963v1 Announce Type: new Abstract: Ship detection in Synthetic Aperture Radar (SAR) images plays an important role for maritime situational awareness, especially with respect to different illegal activities at sea such as illegal fishing, smuggling or border violatio…

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