Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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An approach for automatic classification of computed tomography (CT) medical images is presented in this paper. A vast amount of CT images are produced in modern hospitals due to advances of multi-slice Computed Tomography (CT) Scan which handles up to 64 slices per scan. So, an input image based automatic medical image retrieval system is now a necessity. In this paper, Coiflet wavelets are used to extract feature from the CT images. The extracted features are then classified using Support Vector Machine (SVM) with Radial Basis Function (RBF). The performance of SVM for varying parameters is investigated.
N.T.Renukadevi. 1970. \u201cPerformance Evaluation of SVM a RBF Kernel for Medical Image Classification\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F4): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 107
Country: India
Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision
Authors: N.T.Renukadevi, Dr.P.Thangaraj (PhD/Dr. count: 1)
View Count (all-time): 243
Total Views (Real + Logic): 25750
Total Downloads (simulated): 11217
Publish Date: 1970 01, Thu
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Neural Networks and Rules-based Systems used to Find Rational and
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An approach for automatic classification of computed tomography (CT) medical images is presented in this paper. A vast amount of CT images are produced in modern hospitals due to advances of multi-slice Computed Tomography (CT) Scan which handles up to 64 slices per scan. So, an input image based automatic medical image retrieval system is now a necessity. In this paper, Coiflet wavelets are used to extract feature from the CT images. The extracted features are then classified using Support Vector Machine (SVM) with Radial Basis Function (RBF). The performance of SVM for varying parameters is investigated.
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