Encoder–decoder semantic segmentation models for pressure wound images-Reference-Cited by-同舟云学术

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Encoder–decoder semantic segmentation models for pressure wound images

Published:2022-02-17 Issue:2 Volume:70 Page:75-86
ISSN:1368-2199
Container-title:The Imaging Science Journal
language:en
Short-container-title:The Imaging Science Journal

Author:

Eldem Hüseyin¹^ORCID,Ülker Erkan²^ORCID,Yaşar Işıklı Osman³

Affiliation:

1. Vocational School of Technical Sciences, Computer Technologies Department, Karamanoğlu Mehmetbey University, Karaman, Turkey

2. Faculty of Engineering and Natural Sciences, Department of Computer Engineering, Konya Technical University, Konya, Turkey

3. Karaman Education and Research Hospital, Vascular Surgery Department, Karaman, Turkey

Publisher

Informa UK Limited

Subject

Computer Vision and Pattern Recognition,Media Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/13682199.2022.2163531

Reference83 articles.

1. Human skin wounds: A major and snowballing threat to public health and the economy

2. Computerized segmentation and measurement of chronic wound images

3. Pressure ulcers: Pathophysiology, epidemiology, risk factors, and presentation

4. Association of overweight and obesity with the prevalence and incidence of pressure ulcers: A systematic review and meta-analysis

5. The effect of a pressure ulcer prevention care bundle on nursing workload costs

Cited by 2 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 graph-based superpixel segmentation method for measuring pressure ulcers;IEEE Latin America Transactions;2023-07

2. An image compression approach for efficient pneumonia recognition;The Imaging Science Journal;2023-04-27

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