Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
10K - 100K
ArXiv:
Update README.md
Browse files
README.md
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# Dataset Card for BIOSCAN-30k
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<!-- Provide a quick summary of the dataset. -->
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This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 30000 samples.
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## Dataset Details
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### Dataset Description
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The BIOSCAN-5M dataset is a multimodal collection of over 5.15 million arthropod specimens (98% insects), curated to advance biodiversity monitoring through machine learning. It expands the earlier BIOSCAN-1M dataset by including high-resolution images, DNA barcode sequences, taxonomic labels (phylum to species), geographical locations, specimen size data, and Barcode Index Numbers (BINs). Designed for both closed-world (known species) and open-world (novel species) scenarios, it supports tasks like taxonomic classification, clustering, and multimodal learning.
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**This dataset is a randomly chosen subset of 30,000 samples across all splits from the Cropped 256 dataset**
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Key Features:
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* Images: 5.15M high-resolution microscope images (1024×768px) with cropped/resized versions.
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* Size Metadata: Pixel count, area fraction, and scale factor for specimens.
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- **Curated by:** International consortium led by the Centre for Biodiversity Genomics, University of Guelph, University of Waterloo, and Simon Fraser University.
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- **Funded by :** Government of Canada’s New Frontiers in Research Fund (NFRF), CFI Major Science Initiatives, Walder Foundation, NVIDIA Academic Grant.
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# Dataset Card for BIOSCAN-30k
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This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 30000 samples.
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## Dataset Details
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The BIOSCAN-5M dataset is a multimodal collection of over 5.15 million arthropod specimens (98% insects), curated to advance biodiversity monitoring through machine learning. It expands the earlier BIOSCAN-1M dataset by including high-resolution images, DNA barcode sequences, taxonomic labels (phylum to species), geographical locations, specimen size data, and Barcode Index Numbers (BINs). Designed for both closed-world (known species) and open-world (novel species) scenarios, it supports tasks like taxonomic classification, clustering, and multimodal learning.
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**This dataset is a randomly chosen subset of 30,000 samples across all splits from the Cropped 256 dataset**
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#### Key Features:
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* Images: 5.15M high-resolution microscope images (1024×768px) with cropped/resized versions.
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* Size Metadata: Pixel count, area fraction, and scale factor for specimens.
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### Dataset Description
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- **Curated by:** International consortium led by the Centre for Biodiversity Genomics, University of Guelph, University of Waterloo, and Simon Fraser University.
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- **Funded by :** Government of Canada’s New Frontiers in Research Fund (NFRF), CFI Major Science Initiatives, Walder Foundation, NVIDIA Academic Grant.
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