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Cervical single cell of squamous intraepithelial lesion classification using shape features and extreme learning machine
R. Riries, Winarno, C. N. Asiah, A. Y. Putri, A. B. Suksmono, I. S. Sitanggang, N. A. Setiawan, A. S. Rahaju, E. H. Kusumastuti
- Biophysics and Medical Physics
- Fisika Komputasi
- Ilmu Forensik
- Intelligent Wearable Technologies Group
- Department of Physics
- Faculty of Science and Technology
- Physics
- Pediatric Kidney Research Group
- Kedokteran Molekular
- Pediatric Gastroenterology, Immunology, and Microbiota
- Patologi Anatomi
- Anatomical Pathology
- Department of Anatomical Pathology
- Faculty of Medicine
Research output: Contribution to journal › Conference article › peer-review
3
Citations
(Scopus)