Zebrafish identification with deep CNN and ViT architectures using a rolling training window

Abstract Zebrafish are widely used in vertebrate studies, yet minimally invasive individual tracking and identification in the lab setting remain challenging due to complex and time-variable conditions. Advancements in machine learning, particularly neural networks, offer new possibilities for devel...

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Bibliographic Details
Main Authors: Jason Puchalla, Aaron Serianni, Bo Deng
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-86351-x
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