Automated Routine Colon Cancer Nuclei Classification Using Black Widow Optimization with Deep Learning Model-Reference-Cited by-同舟云学术

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Automated Routine Colon Cancer Nuclei Classification Using Black Widow Optimization with Deep Learning Model

Published:2023-07-15 Issue: Volume: Page:
ISSN:
Container-title:2023 6th International Conference on Engineering Technology and its Applications (IICETA)
language:
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Author:

Ibrahim Karrar¹,Abed Z.²,Alkhafaji Mohammed Ayad³,Alawadi Ahmed Hussien⁴,Sheel Shaid⁵

Affiliation:

1. Al-Zahraa University for Women,Karbala,Iraq

2. Ahl Al Bayt University,Karbala,Iraq

3. National University of Science and Technology,Dhi Qar,Iraq

4. The Islamic university,Najaf,Iraq

5. Medical Technical College, Al-Farahidi University,Baghdad,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10351190/10351191/10351377.pdf?arnumber=10351377

Reference24 articles.

1. Ensembling handcrafted features with deep features: an analytical study for classification of routine colon cancer histopathological nuclei images

2. Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study

3. Residual Attention Generative Adversarial Networks for Nuclei Detection on Routine Colon Cancer Histology Images

4. Deep Learning in Image Classification using Residual Network (ResNet) Variants for Detection of Colorectal Cancer

5. A Machine Learning Approach to Diagnosing Lung and Colon Cancer Using a Deep Learning-Based Classification Framework

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