A new annotated dataset of zebrafish embryo image sequences enables a spatiotemporal transformer to classify fertility at 98% accuracy and detect compound-induced malformations at 92% accuracy.
Environmental Science & Technology58(50), 21942–21953 (2024)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Automated Detection of Abnormalities in Zebrafish Development
A new annotated dataset of zebrafish embryo image sequences enables a spatiotemporal transformer to classify fertility at 98% accuracy and detect compound-induced malformations at 92% accuracy.