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Cervical Cancer Is One Of The Main Reasons Of Death From Cancer In Women. The Complication Of This Cancer Can Be Limited If It Is Diagnosed And Treated At An Early Stage. In This Paper, We Propose A Cervical Cancer Cell Detection And Classification System Based On Convolutional Neural Networks (CNNs). The Cell Images Are Fed Into A CNNs Model To Extract Deep-learned Features. Cervical Cancer Is Screened Using Visual Inspection After Application Of Acetic Acid (VIA), Papanicolaou (Pap) Test, Human Papillomavirus (HPV) Test And Histopathology Test. Inter- And Intra-observer Variability May Occur During The Manual Diagnosis Procedure, Resulting In Misdiagnosis. The Purpose Of This Study Was To Develop An Integrated And Robust System For Automatic Cervix Type And Cervical Cancer Classification Using Deep Learning Techniques.

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