Datasets:
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README.md
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AquaMonitor is a large, multi-modal multi-view image sequence dataset of aquatic invertebrates, collected during two years of operational environmental monitoring. It allows benchmarking computer vision algorithms for fine-grained classification, open-set detection, out-of-distribution detection and domain adaptation, all which are problems encountered in real-life monitoring situations.
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The dataset has 2.7M images from 43,189 specimens, DNA sequences for 1358 specimens, and dry mass and size measurements for 1494 specimens, making it also one of the largest biological multi-view and multi-modal datasets collected with an uniform setup.
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## Uses
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AquaMonitor is a large, multi-modal multi-view image sequence dataset of aquatic invertebrates, collected during two years of operational environmental monitoring. It allows benchmarking computer vision algorithms for fine-grained classification, open-set detection, out-of-distribution detection and domain adaptation, all which are problems encountered in real-life monitoring situations.
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The dataset has 2.7M images from 43,189 specimens, DNA sequences for 1358 specimens, and dry mass and size measurements for 1494 specimens, making it also one of the largest biological multi-view and multi-modal datasets collected with an uniform setup.
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## Dataset Sources
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Dataset handling library: https://github.com/mikkoim/aquamonitor
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Dataset repository: https://github.com/mikkoim/aquamonitor-codes
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Pretrained models: https://huggingface.co/mikkoim/aquamonitor-baselines
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## Uses
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