Accurate and Automated Deep Learning Solution for Skin Cancer Detection
Keywords:
Convolutional neural network, deep learning, generative adversarial networks, image classification, skin cancerAbstract
Cancer of the skin is a major health concern worldwide. In order to aid clinical decision-making, early categorization of skin lesions is essential. This can potentially increase the likelihood of a cure being found for the disease before it progresses to malignancy. However, automatic skin cancer classification is challenging due to the imbalance and scarcity of most skin disease training photos, as well as the model's ability to adapt and be resilient between domains. In this paper, an optimized deep neural network is proposed to enhance disease detection accuracy so that an accurate automated solution can be generated for practitioners. According to the findings of the comparison between the proposed model and other models, the proposed model outperforms the other models.
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