Multi‐Wound Classification: Exploring Image Enhancement and Deep Learning Techniques

Multi‐Wound Classification: Exploring Image Enhancement and Deep Learning Techniques

ABSTRACT Wounds contribute to 30%–42% of hospital visits and 9% of deaths but remain underreported in Africa. Diseases and surgeries increase wound prevalence, especially in rural areas where 27%–82% of people live, and health facilities are poor or non‐existent. This research aims to design a disea...

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Main Authors: Prince Odame, Maxwell Mawube Ahiamadzor, Nana Kwaku Baah Derkyi, Kofi Agyekum Boateng, Kelvin Sarfo‐Acheampong, Eric Tutu Tchao, Andrew Selasi Agbemenu, Henry Nunoo‐Mensah, Dorothy Araba Yakoba Agyapong, Jerry John Kponyo
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Engineering Reports
Subjects:
capsule networks
deep learning
telemedicine
wound classification
Online Access:https://doi.org/10.1002/eng2.70001
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https://doi.org/10.1002/eng2.70001

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