A Bayesian Neo-Normal Mixture Model (Nenomimo) for MRI-Based Brain Tumor Segmentation.
- Published in:
- Applied Sciences (2076-3417), 2020, v. 10, n. 14, p. 4892, doi. 10.3390/app10144892
- By:
- Publication type:
- Article
Works by Pravitasari, Anindya Apriliyanti
Results: 9
1
2
On the YOLOv4 Architecture for Fast and Real Time Congenital Heart Disease Detection Via Ultrasound Videos.
- Published in:
- Matematika, 2022, v. 38, p. 103, doi. 10.11113/matematika.v38.n2.1373
- By:
- Publication type:
- Article
3
Gaussian Mixture Model for MRI Image Segmentation to Build a Three-Dimensional Image on Brain Tumor Area.
- Published in:
- Matematika, 2020, v. 36, p. 217, doi. 10.11113/matematika.v36.n3.1222
- By:
- Publication type:
- Article
4
Framework for Monitoring the Spatiotemporal Distribution and Clustering of the Digital Society Index of Indonesia.
- Published in:
- Sustainability (2071-1050), 2024, v. 16, n. 24, p. 11258, doi. 10.3390/su162411258
- By:
- Publication type:
- Article
5
UNet-VGG16 with transfer learning for MRI-based brain tumor segmentation.
- Published in:
- Telkomnika, 2020, v. 18, n. 3, p. 1310, doi. 10.12928/TELKOMNIKA.v18i3.14753
- By:
- Publication type:
- Article
6
Lung and Infection CT-Scan-Based Segmentation with 3D UNet Architecture and Its Modification.
- Published in:
- Healthcare (2227-9032), 2023, v. 11, n. 1, p. 213, doi. 10.3390/healthcare11020213
- By:
- Publication type:
- Article
7
A Deep Learning Review of ResNet Architecture for Lung Disease Identification in CXR Image.
- Published in:
- Applied Sciences (2076-3417), 2023, v. 13, n. 24, p. 13111, doi. 10.3390/app132413111
- By:
- Publication type:
- Article
8
Enhancing 3D Lung Infection Segmentation with 2D U-Shaped Deep Learning Variants.
- Published in:
- Applied Sciences (2076-3417), 2023, v. 13, n. 21, p. 11640, doi. 10.3390/app132111640
- By:
- Publication type:
- Article
9
Enhancing an Imbalanced Lung Disease X-ray Image Classification with the CNN-LSTM Model.
- Published in:
- Applied Sciences (2076-3417), 2023, v. 13, n. 14, p. 8227, doi. 10.3390/app13148227
- By:
- Publication type:
- Article