Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/1375Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dr. T. S. Poornappriya, Dr. R. Gopinath | - |
| dc.date.accessioned | 2023-08-09T13:40:48Z | - |
| dc.date.available | 2023-08-09T13:40:48Z | - |
| dc.date.issued | 2023-08-08 | - |
| dc.identifier.issn | 1735-188X | - |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1375 | - |
| dc.language.iso | en | en_US |
| dc.subject | Breast Cancer, Mammography, Self-Organizing Map | en_US |
| dc.subject | Euclidean Distance, Validity Measure, Double Bouldin Index. | en_US |
| dc.title | Enhancing Breast Cancer Diagnosis: A Neural Network-Based Clustering Approach For Segmentation | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Department of Business Administration | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| WEBOLOGY 18 (5) - 351.pdf | 261.83 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.