Enhancing Cervical Cancer Classification: Through a Hybrid Deep Learning Approach Integrating DenseNet201 and InceptionV3

This paper proposes a hybrid deep learning model integrating DenseNet201 and InceptionV3 to address the challenges in achieving accurate and reliable cervical cancer classification. Current models often exhibit limitations in balancing precision and recall, which are critical for dependable clinical...

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Ngā kaituhi matua:	Abhiram Sharma, R. Parvathi
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	IEEE 2025-01-01
Rangatū:	IEEE Access
Ngā marau:	Cervical cancer classification deep learning DenseNet201 feature fusion fine tuning hybrid model
Urunga tuihono:	https://ieeexplore.ieee.org/document/10835083/
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!