Explainable automated classification of cervical cancer cells using SE-LGANet with squeeze and excitation blocks and local and global attention mechanisms
A Convolutional Neural Network integrated with Squeeze-and-Excitation blocks and dual attention mechanisms was developed to classify five distinct cell types, providing an explainable and systematically validated approach for cervical cell evaluation.
Ö. F. Alçin, Muzaffer Aslan, Zafer Comert et al.
· Discover Computing · 0 citations