An active-learning based training-schedule for biomedical image segmentation on deep neural networks
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
Hoofdauteurs: | Hassan, Mehadi, Das, Shemonto, Dipu, Shoaib Ahmed |
---|---|
Andere auteurs: | Majumdar, Mahbubul Alam |
Formaat: | Thesis |
Taal: | en_US |
Gepubliceerd in: |
Brac University
2021
|
Onderwerpen: | |
Online toegang: | http://hdl.handle.net/10361/14809 |
Gelijkaardige items
-
Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
door: Sharma, Tanmoyee, et al.
Gepubliceerd in: (2021) -
Exploring deep features: deeper fully convolutional neural network for image segmentation
door: Kamran, Sharif Amit, et al.
Gepubliceerd in: (2017) -
3D Brain image segmentation using 3D tiled convolution neural networks
door: Haque, Md Mahibul, et al.
Gepubliceerd in: (2024) -
A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images
door: Bin Mushfiq, Rahil, et al.
Gepubliceerd in: (2024) -
Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
door: Hossain, Mohammad Sakib, et al.
Gepubliceerd in: (2023)