Abstract:
Skin cancer, which can be lethal, is essentially the improper proliferation of skin tissues.
It has recently developed into one of the most dangerous sorts of additional malignancies
in humans. Early detection may help the patient endure. Skin cancer is notoriously
difficult to detect. Currently, computer vision performs incredibly well when used to
diagnose medical images. Along with technological development and the rapid rise in
computer accessibility, several machine learning algorithms and deep learning algorithms
have been developed for the interpretation of medical images, especially images of skin
lesions. According to our paper, there are five fast-ai CNN pretrained models with
various image pre-processing techniques that enhance the classification capability of skin
lesions and make them more precise than other existing models. The HAM10000
dataset's benign and malignant cancer lesions are distinguished by utilizing a number of
pre-processing methods. The experimental findings showed that the suggested model
improved its accuracy to 97% in both training and testing.
