Skin Disease Detection Using Deep Learning
DOI:
https://doi.org//10.32628/CSEIT2410134Keywords:
Convolutional Neural Network, Deep Learning, EfficientNet, Skin Cancer, Activation Function, Data AugmentationAbstract
Skin diseases are a major public health problem worldwide, requiring effective and timely diagnosis for effective treatment. In this paper, we present a new approach to automatically detect skin diseases using deep learning technology. The model we propose uses a Convolutional Neural Network (CNN) to analyze dermatological images with high accuracy, providing reliable and fast diagnosis. The system was trained on a variety of datasets to provide reliable performance across a variety of skin conditions. Experimental results show that the proposed model outperforms existing methods, demonstrating its potential for integration into clinical settings. Implementation of this deep learning-based skin disease detection system has the potential to revolutionize dermatological diagnostics and provide a cost-effective and scalable solution to improve patient care.
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