MicroFiberDetect: An Application for the Detection of Microfibres in Wastewater Sludge Based on CNNs
Abstract
Microplastics and microfibres are now widespread in aquatic ecosystems, as oceans and rivers. A serious portion of these microplastics come from urban wastewater treatment plants. Traditional methods for detecting and quantifying them are labour-intensive and time-consuming. This paper introduces MicroFiberDetect, a novel application designed to enhance the detection and quantification of microfibres within sludge samples. Leveraging the power of deep learning, this innovative tool provides detection accuracy and insights into the size and colour of each identified fibre. Reducing time and manpower required for analysis while increasing accuracy and throughput. The application has been deployed as a desktop application that allows field experts to quantify and analyse microfibres in sludge samples.
Cite
Text
Pérez et al. "MicroFiberDetect: An Application for the Detection of Microfibres in Wastewater Sludge Based on CNNs." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I28.35366Markdown
[Pérez et al. "MicroFiberDetect: An Application for the Detection of Microfibres in Wastewater Sludge Based on CNNs." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/perez2025aaai-microfiberdetect/) doi:10.1609/AAAI.V39I28.35366BibTeX
@inproceedings{perez2025aaai-microfiberdetect,
title = {{MicroFiberDetect: An Application for the Detection of Microfibres in Wastewater Sludge Based on CNNs}},
author = {Pérez, Félix Martí and Domínguez-Rodríguez, Ana and Ferri, Cèsar and Monserrat, Carlos},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {29682-29684},
doi = {10.1609/AAAI.V39I28.35366},
url = {https://mlanthology.org/aaai/2025/perez2025aaai-microfiberdetect/}
}