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Application of AI Using U-Net in Skin Lesion Segmentation Cover

Application of AI Using U-Net in Skin Lesion Segmentation

Journal of Automation, Mobile Robotics and Intelligent Systems
Volume 20 (2026): Issue 1 (March 2026)
By: Serra Aksoy  
Open Access
|Mar 2026

Figures & Tables

Figure 1.

U-Net Architecture

Figure 2.

Experimental Setup

Figure 3.

Training Loss, Dice Score, and Validation Metrics over 20 Epochs

Figure 4.

Confusion Matrix for Skin Lesion Segmentation

Train and Validation Data

TrainValidationTotal
Images8,0161,99910,015
Masks8,0161,99910,015
Total16,0323,99820,030
DOI: https://doi.org/10.14313/jamris-2026-006 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
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Language: English
Page range: 66 - 73
Submitted on: Jul 15, 2024
|
Accepted on: Aug 22, 2024
|
Published on: Mar 31, 2026
Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
skin lesion,
segmentation,
U-Net,
deep learning,
dermatology,
convolutional neural networks (CNNs)
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Control engineering, metrology and testing,
Mechanical engineering,
Fundamentals of mechanical engineering

© 2026 Serra Aksoy, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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