Galaxy Zoo Volunteer-Labeled Telescope Images

Galaxy Zoo volunteer labels for telescope images of galaxies, curated by Mike Walmsley. The dataset includes images and labels for visible features like spiral arms and galaxy-galaxy collisions, intended for training foundation models.

Use Cases

• Train a computer vision model on galaxy images with volunteer-provided labels for features like spiral arms.
• Build a galaxy classification system using labels for visible morphological features from citizen scientists.
• Analyze label patterns for specific features such as galaxy-galaxy collisions across the image collection.

Strengths

• Labels provided by Galaxy Zoo volunteers, a large-scale citizen science project.
• Data is formatted for machine learning applications, specifically for training foundation models.
• Curated by a known researcher in the field, Mike Walmsley.

Limitations

• Unknown dataset size, row count, and column structure limits reproducibility planning.
• Labels are from volunteer annotations, which may introduce noise or bias compared to expert labels.
• Specific license details and file formats are not provided in the input.

Provenance

Source

Galaxy Zoo citizen science project.

Collection Method

Volunteer labeling of telescope images.

Time Range

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Freshness

Last updated 2025-05-28.

Geography

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