Abstract: Cervical cancer, second only to breast cancer, is one of the cancer is a leading cause death among women. Cervical cancer is a cancer that forms in the cells of the cervix, which is the lower section of the uterus that connects the uterus to the pelvis to the vaginal area Various forms of the papilloma virus (HPV), a sexually transmitted infection that plays a role in cervical cancer. Cervical cancer plays a critical part in the majority of cases. The risk of cervical cancer developing can be reduced by undergoing screenings and receiving a vaccination that protects against HPV infection Cancer prevention is important. The majority of the time, this is accomplished by checking the transformation zones. Cervical pre-cancerous stages can be observed in three different types, and all can transfigure into cancer. As a result, it's crucial to screen cervical anomalies sensibly and have a reliable process to determine if a cervix is normal (healthy) or pre-cancerous. Presently, the test being carried is a Pap smear test, commonly referred as a Pap test, which is a cervical screening procedure. It examines your cervix for the presence of pre - cancerous or cancerous cells. The Pap test's main drawback is that like many it cannot ensure reliable results. A misdiagnosis Pap test showed that there are abnormal cells in the cervix when there aren't any. At present times deep learning is becoming more important alternative for cancer screening. A cervical cancer detection and classification system based on CNN has been proposed. Deep-learned features are acquired using the CNNs model. The method has exhibited exceptional performance, demonstrating the proposed method's strength in delivering an effective tool for cervical cancer classification in clinical settings.
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DOI:
10.17148/IJARCCE.2022.115204
