Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Automated software for counting and measuring Hyalella genus using artificial intelligence
Ist Teil von
Environmental science and pollution research international, 2023-12, Vol.30 (59), p.123603-123615
Ort / Verlag
Berlin/Heidelberg: Springer Berlin Heidelberg
Erscheinungsjahr
2023
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
Amphipods belonging to the
Hyalella
genus are macroinvertebrates that inhabit aquatic environments. They are of particular interest in areas such as limnology and ecotoxicology, where data on the number of
Hyalella
individuals and their allometric measurements are used to assess the environmental dynamics of aquatic ecosystems. In this study, we introduce HyACS, a software tool that uses a model developed with the YOLOv3’s architecture to detect individuals, and digital image processing techniques to extract morphological metrics of the
Hyalella
genus. The software detects body metrics of length, arc length, maximum width, eccentricity, perimeter, and area of
Hyalella
individuals, using basic imaging capture equipment. The performance metrics indicate that the model developed can achieve high prediction levels, with an accuracy above 90% for the correct identification of individuals. It can perform up to four times faster than traditional visual counting methods and provide precise morphological measurements of
Hyalella
individuals, which may improve further studies of the species populations and enhance their use as bioindicators of water quality.