Translating pixels into identification: Cutting-edge microalgae detection and instance segmentation by leveraging YOLO models

This study harnesses the advanced capabilities of the YOLOv11 model to enhance real-time detection and instance segmentation of microalgae species, specifically Chlorella vulgaris FSP-E, Chlamydomonas reinhardtii, and Spirulina platensis. Comprehensive evaluations revealed that the original RGB data...

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Detalhes bibliográficos

Principais autores:	Jun Wei Roy Chong, Kuan Shiong Khoo, Huong-Yong Ting, Koji Iwamoto, Zengling Ma, Pau Loke Show
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2026-05-01
coleção:	Ecological Informatics
Assuntos:	Microalgae Detection Instance segmentation YOLOv7 YOLOv8 YOLOv11
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S1574954126001585
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