A Comparative Study of Skin Cancer Image Classification Techniques
This study evaluates various deep learning models for skin cancer classification using the HAM10000 dataset, demonstrating that a hybrid model and ResNet50 achieve superior accuracy (99.78% and 99.88%, respectively) compared to other techniques, thereby highlighting their potential to enhance early diagnosis and resource allocation in dermatology.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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