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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.17518455 |
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Table of Contents:
- <p>The dataset was generated during the development of the <strong>FHA-MTT algorithm</strong>, which aims to enable automated health assessment of fish based on swimming behavior. It includes video recordings of <strong>crucian carp (Carassius auratus)</strong> exhibiting both healthy and diseased states, together with <strong>annotation files</strong> used for training object detection and keypoint recognition models. In addition, the dataset contains <strong>tracking results</strong> produced by different multi-object tracking algorithms.</p> <p> FHA-MTT integrates object and keypoint detection with trajectory-based behavioral analysis, providing an efficient and reliable framework for evaluating the health status of fish in aquaculture environments.</p>