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Early Stage of Cervical Cancer Detection Using YOLOv5

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dc.contributor.author Ontor, Md. Zahid Hasan
dc.date.accessioned 2022-09-04T05:14:42Z
dc.date.available 2022-09-04T05:14:42Z
dc.date.issued 2022-02-20
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8565
dc.description.abstract Cervical cancer is a very familiar disease all over the world. It is the tacit slayer. For this many women lose their life. Early detection of cancer cells can save many lives. To do this we have collected some cervical cancer pap-smear test image data. After preprocessing and labeling these data we applied a deep learning model called yolov5. The model has four versions, from these we have applied three versions. All of the model's variations performed admirably. We are the first authors who are working to detect cervical cancer cells by applying the yolov5 model, and we were able to detect cervical cancer cells with a pap-smear test data set both from image and video data. The model can effectively detect cervical cancer photos, according to the findings of the experiments. In the medical field, our study will be quite useful. It can be a good option for radiologists and help them make the best selections possible. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Disease susceptibility en_US
dc.subject Cervical cancer en_US
dc.title Early Stage of Cervical Cancer Detection Using YOLOv5 en_US
dc.type Thesis en_US

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