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• W3195378045 abstract "With the advancement of IoT technology, more and more healthcare applications were developed in recent years. In addition to the traditional sensor-based systems, image-based healthcare IoT systems become more popular since no specialized sensors are required. Combining with Deep Neural Network (DNN) based automated diagnosis and decision-making systems, it is possible to provide users with 24/7 health monitoring in real life. However, the high computational cost for training DNNs can be a hurdle for developing such kind of powerful systems. While cloud computing can be a feasible solution, uploading training data for the DNN models to the cloud may lead to data security issues. In this chapter, we will review some image-based healthcare IoT systems and discuss some potential risks on data security when training the DNN models on the cloud." @default.
• W3195378045 created "2021-08-30" @default.
• W3195378045 creator A5080180158 @default.
• W3195378045 date "2021-10-10" @default.
• W3195378045 modified "2023-09-23" @default.
• W3195378045 title "Data Security Challenges in Deep Neural Network for Healthcare IoT Systems" @default.
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• W3195378045 doi "https://doi.org/10.1007/978-3-030-85428-7_2" @default.
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