Breast Cancer Diagnosis Using Lightweight Deep Convolution Neural Network Model-Reference-Cited by-同舟云学术

Breast Cancer Diagnosis Using Lightweight Deep Convolution Neural Network Model

Published:2023 Issue: Volume:11 Page:124869-124886
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kausar Tasleem¹^ORCID,Lu Yun²^ORCID,Kausar Adeeba³

Affiliation:

1. Mirpur Institute of Technology, Mirpur University of Science and Technology, (MUST), Mirpur, Azad Jammu and Kashmir, Pakistan

2. School of Computer Science and Engineering, Huizhou University, Huizhou, China

3. Department of Information Engineering Technology, Superior University, Lahore, Punjab, Pakistan

Funder

Joint Fund of Basic and Applied Basic Research Fund of Guangdong Province

Fund which aims to Improve Scientific Research Capability of Key Construction Disciplines in Guangdong Province ‘‘Light-Weight Federal Learning Paradigm and its Application’’

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10290886.pdf?arnumber=10290886

Reference72 articles.

1. SA-GAN: Stain Acclimation Generative Adversarial Network for Histopathology Image Analysis

2. Histopathological Breast-Image Classification Using Local and Frequency Domains by Convolutional Neural Network

3. Recent Trends in Computer Assisted Diagnosis (CAD) System for Breast Cancer Diagnosis Using Histopathological Images

4. Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model

5. A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification

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