Datasets › Retina Benchmark

Retina Benchmark

Introduced by Neil Band et al. in Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks23 Nov 2022 archive 2025-07-28

The Retina Benchmark is a set of real-world tasks that accurately reflect such complexities and are designed to assess the reliability of predictive models in safety-critical scenarios. Specifically, two publicly available datasets of high-resolution human retina images exhibiting varying degrees of diabetic retinopathy, a medical condition that can lead to blindness, are used to design a suite of automated diagnosis tasks that require reliable predictive uncertainty quantification.

Source: Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks

Image Source: https://arxiv.org/pdf/2211.12717v1.pdf

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

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Variants archive 2025-07-28

  • Retina Benchmark

1 variant name, as the archive lists them.

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