Vision transformer for skin cancer classification

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No. 33(155) (2023): 1st ISPC «Modern Knowledge: Research and Discoveries» (May 19-20, 2023; Vancouver, Canada).
Section
Information and Web technologies
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Published: May 19, 2023
DOI: https://doi.org/10.51582/interconf.19-20.05.2023.039
Keywords:
skin cancer Machine learning computer vision vision transformer attention convolutional neural networks

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Vladyslav Nikitin
«Igor Sikorsky Kyiv Polytechnic Institute»; Ukraine
Nataliia Shapoval
«Igor Sikorsky Kyiv Polytechnic Institute»; Ukraine

Abstract

This paper investigates the use of vision transformers (ViT) for skin cancer classification tasks, compared to convolutional models. We propose a novel ViT architecture that effectively classifies skin cancer images. Our findings suggest that ViT models have the potential to outperform convolutional models, especially with larger datasets.


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How to Cite
Nikitin, V., & Shapoval, N. (2023). Vision transformer for skin cancer classification. Scientific Collection «InterConf+», (33(155), 449–460. https://doi.org/10.51582/interconf.19-20.05.2023.039

References

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Chen, C.-F., Fan, Q. and Panda, R. (2021) Crossvit: Cross-attention multi-scale vision transformer for Image Classification, arXiv.org. Available at: https://arxiv.org/abs/2103.14899 (Accessed: May 1, 2023). DOI: https://doi.org/10.1109/ICCV48922.2021.00041

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