CACDU-Net: A Novel DoubleU-Net Based Semantic Segmentation Model for Skin Lesions Detection in Images-Reference-Cited by-同舟云学术

CACDU-Net: A Novel DoubleU-Net Based Semantic Segmentation Model for Skin Lesions Detection in Images

Author:

Hao Shengnan¹,Wu Haotian¹^ORCID,Du Chengyuan¹,Zeng Xinyi¹,Ji Zhanlin¹^ORCID,Zhang Xueji²,Ganchev Ivan³^ORCID

Affiliation:

1. Hebei Key Laboratory of Industrial Intelligent Perception, North China University of Science and Technology, Tangshan, China

2. School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen, China

3. Telecommunications Research Centre (TRC), University of Limerick, Limerick, Ireland

Funder

National Key Research and Development Program of China

Bulgarian National Science Fund

Telecommunications Research Centre (TRC), University of Limerick, Ireland

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

Reference54 articles.

Cited by 3 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. A Deep Learning Based Critical Analysis Of Skin Lesion Classification;2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE);2024-05-16

3. Skin Lesion Segmentation Using U-Net With Different Backbones: Comparative Study;2023 IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI);2023-12-13