Hybrid Convolution-Transformer models for breast cancer classification using histopathological images
Author:
Affiliation:
1. FERHAT ABBES SETIF-1 University,LIS Laboratory,Electronic Department,Setif,Algeria
2. M’Sila University,Electrical Engineering Laboratory LGE,M’sila,28000
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10099471/10100354/10100518.pdf?arnumber=10100518
Reference20 articles.
1. Mlp-mixer: An all-mlp architecture for vision;tolstikhin;Advances in neural information processing systems,2021
2. Transformers in Vision: A Survey
3. Pytorch: An imperative style, high-performance deep learning library;paszke;Advances in neural information processing systems,2019
4. A Dataset for Breast Cancer Histopathological Image Classification
5. DRDA-Net: Dense residual dual-shuffle attention network for breast cancer classification using histopathological images
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Enhancing Breast Cancer Histopathological Image Classification using Attention-Based High Order Covariance Pooling;2023-08-17
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