Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021
Asıl Yazarlar: | Sharma, Tanmoyee, Tabassum, Zaharat, Banik, Ritu, Rahman, S.M.Arifur |
---|---|
Diğer Yazarlar: | Mohsin, Abu S.M. |
Materyal Türü: | Tez |
Dil: | English |
Baskı/Yayın Bilgisi: |
Brac University
2021
|
Konular: | |
Online Erişim: | http://hdl.handle.net/10361/15142 |
Benzer Materyaller
-
A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images
Yazar:: Bin Mushfiq, Rahil, ve diğerleri
Baskı/Yayın Bilgisi: (2024) -
An active-learning based training-schedule for biomedical image segmentation on deep neural networks
Yazar:: Hassan, Mehadi, ve diğerleri
Baskı/Yayın Bilgisi: (2021) -
Semantic segmentation with attention dense U-net for lung extraction from X-ray images
Yazar:: Auvy, Akib Al Mahmud, ve diğerleri
Baskı/Yayın Bilgisi: (2023) -
Exploring deep features: deeper fully convolutional neural network for image segmentation
Yazar:: Kamran, Sharif Amit, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Pyramid pooling enhanced ResUNet for accurate 3D brain image segmentation
Yazar:: Mollah, Md. Shawon, ve diğerleri
Baskı/Yayın Bilgisi: (2024)