ABC-YOLO: Automated skin burn depth classification using YOLO architectures

Uğur Şevik; Onur Mutlu

doi:10.1371/journal.pone.0344042

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Open Access

Peer-reviewed

Research Article

ABC-YOLO: Automated skin burn depth classification using YOLO architectures

Uğur Şevik ,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: usevik@ktu.edu.tr

Affiliations Department of Computer Science, Faculty of Science, Karadeniz Technical University, Trabzon, Türkiye, Retina R&D Software and Engineering Services Ltd., Trabzon Teknokent, Trabzon, Türkiye

https://orcid.org/0000-0002-2056-9988

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Onur Mutlu

Roles Investigation, Resources, Visualization

Affiliations Department of Computer Science, Faculty of Science, Karadeniz Technical University, Trabzon, Türkiye, Retina R&D Software and Engineering Services Ltd., Trabzon Teknokent, Trabzon, Türkiye

https://orcid.org/0009-0004-6204-5535

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ABC-YOLO: Automated skin burn depth classification using YOLO architectures

Uğur Şevik,
Onur Mutlu

Published: March 18, 2026
https://doi.org/10.1371/journal.pone.0344042

About the Authors

Uğur Şevik

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: usevik@ktu.edu.tr

Affiliations Department of Computer Science, Faculty of Science, Karadeniz Technical University, Trabzon, Türkiye, Retina R&D Software and Engineering Services Ltd., Trabzon Teknokent, Trabzon, Türkiye

https://orcid.org/0000-0002-2056-9988

Onur Mutlu

Roles Investigation, Resources, Visualization

https://orcid.org/0009-0004-6204-5535

Competing Interests

The authors have declared that no competing interests exist.

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Burns
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Deep learning
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Computer architecture
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Neck
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Machine learning algorithms
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