Datasets:
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README.md
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@@ -46,6 +46,8 @@ The SAVMAP dataset comprises ultrahigh-resolution aerial imagery captured by unm
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⚠️ **This version of the dataset includes improved annotations** to address issues found in the original Micromappers campaign, which was known to include many false positives. The updated annotations were curated and validated by **Paul Allin**, a PhD candidate at **Stellenbosch University (South Africa)**, providing a more accurate basis for training and evaluating computer vision models in ecological monitoring tasks.
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## Supported Tasks and Use Cases
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- **Object Detection**: Training and evaluation of animal detection models in ultrahigh-resolution aerial imagery.
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⚠️ **This version of the dataset includes improved annotations** to address issues found in the original Micromappers campaign, which was known to include many false positives. The updated annotations were curated and validated by **Paul Allin**, a PhD candidate at **Stellenbosch University (South Africa)**, providing a more accurate basis for training and evaluating computer vision models in ecological monitoring tasks.
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⚠️ **Disclaimer**: this dataset is not identical to the "version 2" hosted on Zenodo.org. The images have been cropped to 2000*2000 and only a portion of the negative samples (i.e. empty images) have been selected. The dataset comprises 3545 negative samples and 379 positive samples.
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## Supported Tasks and Use Cases
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- **Object Detection**: Training and evaluation of animal detection models in ultrahigh-resolution aerial imagery.
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