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Data · dataset · 2026

Hamlyn-C

Listed in Teesside University Research Data Repository

The dataset Hamlyn-C is introduced in the context of assessing robustness in endoscopic depth prediction models.

Description

It is inspired on EndoDepth benchmark, which is designed to evaluate the performance of monocular depth prediction models specifically for endoscopic scenarios. The dataset features 16 different types of image corruptions, each with 5 levels of severity, encompassing challenges like lens distortion, resolution alterations, specular reflection, and color changes that are typical in endoscopic imaging.

The ground truth is on the original testing set of Hamlyn. The purpose of Hamlyn-C is to test the robustness of depth estimation models by exposing them to various common endoscopic corruptions. This dataset is a valuable tool for developing and evaluating depth prediction algorithms that can handle the unique challenges presented by endoscopic procedures, ensuring more accurate and reliable outcomes in medical imaging.

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Image 75% · Imaging 75%
Provenance · 1 source records, 9 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/prsfx6sgnf.111 h agoJSON v1
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