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Image Dataset of Microfauna in Activated Sludge

  • Zheng Pang
  • , Aijie Wang
  • , Ying Chen
  • , Tiefu Xu*
  • , Zhiming Shao
  • , Chang Ge
  • , Chuan He
  • , Yu Tao*
  • *Corresponding author for this work
  • CAS - Research Center for Eco-Environmental Sciences
  • University of Chinese Academy of Sciences
  • Harbin Institute of Technology
  • School of Environment, Harbin Institute of Technology
  • Heilongjiang University
  • CAS - Institute of Automation
  • CAS - Institute of Hydrobiology

Research output: Contribution to journalArticlepeer-review

Abstract

Microfauna play a crucial role in the ecological functioning and monitoring of activated sludge systems. However, existing studies often rely on manual observation and lack standardized image datasets for developing automated recognition models. Here, we present a Microfauna Dataset in Activated Sludge (MD-AS-2025), a publicly available image dataset designed to support object detection, classification, and related computer vision tasks. The dataset comprises two components: an annotated dataset (Dataset A) containing 4,000 full-frame microscopic images labeled across five morphologically and ecologically distinct microfaunal groups, and a cropped dataset (Dataset B), consisting of 14,257 single-object images generated from model-assisted detection and manual verification. All images were acquired under realistic activated sludge conditions using a high-throughput imaging system. The dataset reflects practical functional groupings commonly used in activated sludge analysis. MD-AS-2025 offers a reusable and extensible resource for developing intelligent microfauna analysis tools and provides a scalable framework for dataset construction in aquatic environments.

Original languageEnglish
Article number1972
JournalScientific Data
Volume12
Issue number1
DOIs
StatePublished - Dec 2025
Externally publishedYes

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