Brain Tumor Segmentation Using Ensemble CNN-Transfer Learning Models: DeepLabV3plus and ResNet50 Approach
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63772-8_30
Reference42 articles.
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2. Akcay, O., Kinaci, A.C., Avsar, E.O., Aydar, U.: Semantic segmentation of high-resolution airborne images with dual-stream DeepLabV3+. ISPRS Int. J. Geo Inf. 11(1), 23 (2021). https://doi.org/10.3390/ijgi11010023
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4. Badža, M.M., Barjaktarović, M.Č: Segmentation of brain tumors from MRI images using convolutional autoencoder. Appl. Sci. 11(9), 4317 (2021). https://doi.org/10.3390/app11094317
5. Beliveau, V., Nørgaard, M., Birkl, C., Seppi, K., Scherfler, C.: Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging. Hum. Brain Mapp. 42(15), 4809–4822 (2021). https://doi.org/10.1002/hbm.25604
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