FPDANet combines a ResNet backbone with dual attention and bilateral feature fusion to reach 91.05% top-1 accuracy on 21 fetal ultrasound view classes, but the architecture reuses known modules without citation and the evaluation lacks code, data, and error bars.
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FPDANet: A Multi-Section Classification Model for Intelligent Screening of Fetal Ultrasound
FPDANet combines a ResNet backbone with dual attention and bilateral feature fusion to reach 91.05% top-1 accuracy on 21 fetal ultrasound view classes, but the architecture reuses known modules without citation and the evaluation lacks code, data, and error bars.