Transformer in Microbial Image Analysis: A Comparative Exploration of TransUNet, UNet, and DoubleUNet for SEM Image Segmentation-Reference-Cited by-同舟云学术

Transformer in Microbial Image Analysis: A Comparative Exploration of TransUNet, UNet, and DoubleUNet for SEM Image Segmentation

Published:2023-12-05 Issue: Volume: Page:4500-4502
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
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Author:

Shrestha Gurung Bichar Dip¹,Khanal Anup¹,Hartman Timothy W.¹,Do Tuyen¹,Chataut Sandeep¹,Lushbough Carol¹,Gadhamshetty Venkataramana²,Gnimpieba Etienne Z.¹

Affiliation:

1. University of South Dakota,Dept. of Biomedical Engineering,Vermillion,USA

2. South Dakota Mines,Two-Dimensional Materials for Biofilm Engineering Science and Technology (2DBEST) Center,Rapid City,SD,United States

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385974.pdf?arnumber=10385974

Reference8 articles.

1. CryoTransformer: A Transformer Model for Picking Protein Particles from Cryo-EM Micrographs;Dhakal;bioRxiv,2023

2. Chapter 19 - Microbial Corrosion of Iron;Iverson;Microbial Iron Metabolism,1974

3. U-Net Based Image Segmentation Techniques for Development of Non-Biocidal Fouling-Resistant Ultra-Thin Two-dimensional (2D) Coatings

4. Survey on semantic image segmentation techniques

5. ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness;Geirhos,2018

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