DCAVN: Cervical cancer prediction and classification using deep convolutional and variational autoencoder network

Early detection, early diagnosis and classification of the cancer type facilitates faster disease management of patients. Cervical cancer is fourth most pervasive cancer type which affects life of many people worldwide. The intent of this study is to automate cancer diagnosis and classification thro...

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Veröffentlicht in:	Multimedia tools and applications Jg. 80; H. 20; S. 30399 - 30415
Hauptverfasser:	Khamparia, Aditya, Gupta, Deepak, Rodrigues, Joel J. P. C., de Albuquerque, Victor Hugo C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.08.2021 Springer Nature B.V
Schlagworte:	Cancer Cervical cancer Classification Computer Communication Networks Computer Science Data Structures and Information Theory Deep learning Diagnosis Machine learning Medical diagnosis Multimedia Information Systems Pap smear Special Purpose and Application-Based Systems Training Deep learning Variational Convolution Autoencoder Cervical
ISSN:	1380-7501, 1573-7721
Online-Zugang:	Volltext
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