Abscissa-Ordinate Focused Network for Psoriasis and Eczema Healthcare Cyber-Physical System With Active Label Smoothing

Autor: Wei Zhu, Huilin Lai, Haitang Zhang, Guokai Zhang, Yongxin Luo, Jie Wang, Lu Sun, Jianwei Lu, Shuihua Wang, Yanwei Xiang
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Access, Vol 12, Pp 54953-54963 (2024)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3384310
Popis: With psoriasis and eczema being the two most common diseases worldwide, achieving automatic diagnosis could be useful for healthcare cyber-physical system. However, creating such an automatic classification system is still challenging since it cannot learn positional and spatial information from unstable training. In this paper, we propose a novel abscissa-ordinate focused network (AOFNet) with active label smoothing for the identification of psoriasis and eczema from images. The AOFNet incorporates the developed abscissa-ordinate focused module that focuses on abscissa-ordinate information and leverages the attention mechanism to enhance the network’s ability to learn positional and spatial details, resulting in improved classification performance. Additionally, the adoption of an active label smoothing approach effectively mitigates the problem of overconfidence and effectively captures the dynamic changes that occur during training, thereby providing an added boost to the overall performance of the network. To evaluate the proposed healthcare cyber-physical system, extensive experiments are conducted on the clinical psoriasis and eczema dataset, and the results demonstrate that the designed system could gain comparable classification performance.
Databáze: Directory of Open Access Journals