METHOD OF CLASSIFYING IMAGES OF MOLES FOR DETECTING MELANOMA

Authors

  • Kristina Hrabenko National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Ukraine
  • Vladyslav Taran National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute", Ukraine

Keywords:

melanoma, dermoscopy, convolutional neural network, transfer learning, EfficientNet, image classification, Grad-CAM

Abstract

The article presents method for automatic malignant melanoma detection based on dermoscopic images. The subsystem is built on the EfficientNet-B0 convolutional neural network for classifying skin lesions as benign or malignant, while the Grad-CAM method is used to visualize and interpret the model’s decisions.

References

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Mittal, B. (2024). Melanoma Cancer Image Dataset. Kaggle. https://www.kaggle.com/datasets/bhaveshmittal/melanoma-cancer-dataset/data

Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2017). Grad-CAM: Visual explanations from deep networks via gradient-based localization. Proceedings of the IEEE International Conference on Computer Vision (ICCV 2017), 618–626. https://doi.org/10.1109/ICCV.2017.74

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Published

2026-05-08

Issue

Section

Machine learning, Big Data (AI)