Institution profile

Pioneer Centre for Artificial Intelligence

Academic institutioneurope · dk
Official website
Research library2linked papers
Opportunities0open roles
Selected work

Representative Papers

A Multi-Annotator Study of Segmentation Noise and Uncertainty in Turbid Underwater Images

Aug 15, 2026

This study addresses annotation uncertainty and noise in turbid underwater image segmentation through a large-scale multi-annotator investigation involving over one hundred participants. By systematically analyzing noise sources across varying turbidity levels via controlled experiments, privileged information assistance, and ensemble strategies, this work reveals systematic error patterns induced by turbidity in real-world underwater scenarios for the first time. Furthermore, it proposes effective methods to enhance annotation quality and releases an open-source dataset. This research bridges a critical gap in understanding annotation uncertainty within underwater segmentation, providing both theoretical foundations and practical guidelines for constructing high-quality underwater vision benchmarks.

0 citationsRead paper
Recent publications

Latest Papers

A Multi-Annotator Study of Segmentation Noise and Uncertainty in Turbid Underwater Images

Aug 15, 2026

This study addresses annotation uncertainty and noise in turbid underwater image segmentation through a large-scale multi-annotator investigation involving over one hundred participants. By systematically analyzing noise sources across varying turbidity levels via controlled experiments, privileged information assistance, and ensemble strategies, this work reveals systematic error patterns induced by turbidity in real-world underwater scenarios for the first time. Furthermore, it proposes effective methods to enhance annotation quality and releases an open-source dataset. This research bridges a critical gap in understanding annotation uncertainty within underwater segmentation, providing both theoretical foundations and practical guidelines for constructing high-quality underwater vision benchmarks.

0 citationsRead paper