Abstract
In this paper, we developed cloud-based skin lesion diagnosis system using convolutional neural networks, which consists of the following: (a) Deep learning based classifier that processes user submitted lesion images which runs on a server connected to the cloud based database. (b) Deep learning based classifier performs quality checks and filters user requests before the request is sent off to the diagnosis classifier. (c) A mobile application that runs on Android and iOS platforms to showcase the system. We designed and implemented the system’s architecture.
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Acknowledgments
The authors gratefully acknowledge funding from NSF award No. 1464537, Industry/University Cooperative Research Center, Phase II under NSF 13-542. We are also thankful to Farris Foundation who also provided funds for this project.
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Akar, E., Marques, O., Andrews, W.A., Furht, B. (2019). Cloud-Based Skin Lesion Diagnosis System Using Convolutional Neural Networks. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham. https://doi.org/10.1007/978-3-030-22871-2_70
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DOI: https://doi.org/10.1007/978-3-030-22871-2_70
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