1. Skin cancer recognition using CNN.
- Author
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Jyothiswar, Challa, Kumar, Ravula Ganesh, and Kalaivani, J.
- Subjects
- *
SKIN cancer , *HEALTH services accessibility , *TECHNOLOGICAL innovations , *CAMERA phones , *INTERNET access - Abstract
People can now access the internet from anywhere in the world thanks to technological advancements. However, access to health care in remote areas is currently limited. The proposed solution is intended to bridge the gap between specialistsand patients. This prototype will be able to identify cancer of the skin from photos taken using a camera or phone. To process the network and produce more precise results, cloud servers are used. On the server side, the Deep Residual Learning model was employed to estimate the likelihood of malignancy. ResNet has three parametric layers. Each layer includes CNN, Batch Normalizations and Max-pooling. On the ISIC - 2017 challenge, the model currently has an accuracy of 89%. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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