Community-aware evaluation and threshold calibration for open-set plankton image recognition
Automated plankton image recognition is increasingly used in aquatic ecosystem monitoring, but deployed classifiers inevitably encounter unseen taxa and non-target particles. Open-set recognition methods are usually evaluated with sample-level metrics such as AUROC, AUPR, and FPR@95% unknown-recall operating points, whereas ecological monitoring depends on community-level estimates of taxon abundance and diversity. This study examines the mismatch between these objectives using controlled pseudo-communities and three datasets spanning marine zooplankton imaged by ZooScan, marine phytoplankton imaged by IFCB, and freshwater plankton imaged by an in-situ camera. We define Open-Set Community...
| Authors | Xi Chen, Eryuan Huang, Yingjun Xiao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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