CERVICAL CANCER USING MULTIKERNAL SUPPORT VECTOR MACHINE

Abstract

Cervical cancer is one of the deadliest cancers known and is additionally a key research territory in picture preparing. The fundamental issue with this cancer is that it can't be identified as it doesn't toss any manifestations until the last stages. This is ascribed to the cancer itself and furthermore to the absence of pathologists accessible to screen the cancer. Here we have proposed a novel way to deal with characterize the different malignancies in cervical pictures utilizing acoustic shadowing. For arrangement we have utilized MKSVM classifier that would help us to order the phases of the cancer and enable the pathologist to distinguish the cancer better. The proposed picture has been tried with an arrangement of pictures and has turned out to be proficient.