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Hafsa Boudraa

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Conference Open access 2026

Benchmarking CNN Architectures for Cervical Cell Classification: A Unified Transfer Learning Framework on SIPaKMeD

This work evaluates five pre-trained CNN architectures- ResNet50, EfficientNetB0, DenseNet121, InceptionV3, and MobileNetV2- on the SIPaKMeD cervical cell dataset, within a unique, controlled experimental framework, providing a repeatable starting point for subsequent optimization work.

Hanane N'ait Taleb, Hafsa Boudraa, A. Tannouche et al. · 0 citations

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