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Cervical cancer detection using SVM based feature screening
Jiayong Zhang,
Yanxi Liu
Huck Institutes of the Life Sciences
Electrical Engineering
Computer Science and Engineering
Research output
:
Contribution to journal
›
Conference article
›
peer-review
70
Scopus citations
Overview
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Dive into the research topics of 'Cervical cancer detection using SVM based feature screening'. Together they form a unique fingerprint.
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Keyphrases
Screening Method
100%
Feature Screening
100%
Cervical Cancer Screening
100%
SVM-based
100%
Classification Accuracy
50%
Support Vector Machine
50%
Computational Efficiency
50%
Relevance Ranking
50%
Variance Ratio
50%
Independence Assumption
50%
Pixel Classification
50%
Texture Features
50%
Information Gain
50%
Screening Algorithm
50%
Decision Boundary
50%
Computer Science
Support Vector Machine
100%
Experimental Result
50%
Computational Efficiency
50%
Classification Accuracy
50%
Information Gain
50%
Texture Feature
50%
Bottom-Up Approach
50%
Variance Ratio
50%
Engineering
Texture Feature
100%
Decision Boundary
100%