A selective mitigation technique of soft errors for DNN models used in healthcare applications: DenseNet201 case study

• Main Authors: Adam, Khalid, Izzeldin, I. Mohd, Ibrahim, Younis
• Format: Article
• Language: English
• Published: IEEE 2021
• Subjects: QA76 Computer software; T Technology (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/31730/1/A%20selective%20mitigation%20technique%20of%20soft%20errors.pdf; http://umpir.ump.edu.my/id/eprint/31730/; https://doi.org/10.1109/ACCESS.2021.3076716; https://doi.org/10.1109/ACCESS.2021.3076716

Deep neural networks (DNNs) have been successfully deployed in widespread domains, including healthcare applications. DenseNet201 is a new DNN architecture used in healthcare systems (i.e., presence detection of the surgical tool). Specialized accelerators such as GPUs have been used to speed up the...