Encoder Enhanced Atrous (EEA) Unet architecture for Retinal Blood vessel segmentation

Author:

V. Sathananthavathi,G. Indumathi

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Experimental and Cognitive Psychology,Software

Reference38 articles.

1. Alom, M. Z., Hasan, M., Yakopcic, C., Taha, T. M., & Asari, V. K. (2018). Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation. arXiv: 1802.06955.

2. A state-of-the-art survey on deep learning theory and architectures;Alom;Electronics,2019

3. Convolutional neural network with batch normalization for glioma and stroke lesion detection using MRI;Amin;Cognitive Systems Research,2020

4. A performance comparison between shallow and deeper neural networks supervised classification of tomosynthesis breast lesions images;Bevilacqua;Cognitive Systems Research,2019

5. Retinal vessels segmentation based on a convolutional neural network;Brancati,2018

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