FoSoHA-Net: Deep Learning for Accurate Breast Cancer Classification Leveraging Hybrid Attention Mechanisms-Reference-Cited by-同舟云学术

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FoSoHA-Net: Deep Learning for Accurate Breast Cancer Classification Leveraging Hybrid Attention Mechanisms

Published:2024-05-17 Issue: Volume:8 Page:152-156
ISSN:
Container-title:2024 2nd International Conference on Intelligent Perception and Computer Vision (CIPCV)
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Author:

Addo Daniel¹,Al-Antari Mugahed A.²,Zhou Shijie¹,Ashalley Eric³,Muoka Gladys Wavinya¹,Nartey Obed T.⁴

Affiliation:

1. University of Electronic Science and Technology of China,School of Information and Software Engineering,Chengdu,China,610054

2. Sejong University,AISSLab,Department of Artificial Intelligence and Data Science,Seoul,Republic of Korea

3. University of Electronic Science and Technology of China,Chengdu,China,610054

4. Sino-British Collaborations, Erxianqiao Campus,ChengduUniversity of Technology of China,Chengdu,China,610059

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10623929/10623942/10623977.pdf?arnumber=10623977

Reference16 articles.

1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

2. Comparison of the performance of machine learning algorithms in breast cancer screening and detection: A protocol;Salod;Journal of public health research,2019

3. Breast cancer detection by leveraging Machine Learning

4. Breast cancer detection using Histopathology Image with Mini-Batch Stochastic Gradient Descent and Convolutional Neural Network

5. A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images;Zakareya;Diagnostics,2023

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