Classification of fibroid using novel fully connected CNN with back propagation classifier (NFCCNNBP)
- Title
- Classification of fibroid using novel fully connected CNN with back propagation classifier (NFCCNNBP)
- Creator
- Devi M.R.; Sivakumar V.; Sindhu V.; Nataraj C.; Kanna R.R.; Karthikeswaran D.
- Description
- In this phase, we utilize features extracted from a prior stage to classify uterine fibroids. We employ a predefined dataset with feature values as our training set for a novel classifier called the "Novel Fully Connected CNN with Back Propagation Classifier."This classifier learns from the training set. We then put this method to the test with new images not included in the training dataset. Its primary objective is to assess the extent of infection across the entire uterine surface. Through the adoption of a Convolutional Neural Network (CNN) combined with Back Propagation (BP), we have achieved an impressive accuracy rate of 98.3% for predictions. When we compare this accuracy to existing classifiers like Fuzzy Logic, Naive Bayes, and SVM, our proposed model, NFCCNNBP, outperforms them significantly. 2024 Author(s).
- Source
- AIP Conference Proceedings, Vol-3161, No. 1
- Date
- 2024-01-01
- Publisher
- American Institute of Physics
- Coverage
- Devi M.R., School of Information Science, Presidency University, Bangalore, India; Sivakumar V., School of Computing, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Sindhu V., Department of Computer Science, CHRIST University, Bangalore, India; Nataraj C., School of Computing, Faculty of Computing Engineering and Technology, Asia Pacific University of Technology and Innovation, Kuala Lumpur, Malaysia; Kanna R.R., Department of Computer Science, CHRIST University, Bangalore, India; Karthikeswaran D., Department of Information Technology, Nehru Institute of Technology, Coimbatore, India
- Rights
- Restricted Access
- Relation
- ISSN: 0094243X
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Devi M.R.; Sivakumar V.; Sindhu V.; Nataraj C.; Kanna R.R.; Karthikeswaran D., “Classification of fibroid using novel fully connected CNN with back propagation classifier (NFCCNNBP),” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/18950.