![]() ![]() The purpose of the project is to show the potential of Spatial Computing, Artificial Intelligence, and the Internet of Things for medical support systems such as diagnosis systems.Īlthough the classifier used in this project is very accurate and shows good results both on paper and in real world testing, it is not meant to be an alternative to professional medical diagnosis.ĭevelopers that have contributed to this repository have experience in using Artificial Intelligence for detecting certain types of cancer & COVID-19. This project should be used for research purposes only. We use the trained model from COVID-19 Tensorflow DenseNet Classifier with the COVID-19 Tensorflow DenseNet Classifier For Raspberry Pi 4 and serve an API endpoint that exposes the Artificial Intelligence classifier allowing Magic Leap 1 to communicate with it. The project uses the COVID-19 Tensorflow DenseNet Classifier a Tensorflow implementation of DenseNet and the SARS-COV-2 Ct-Scan Dataset, a large dataset of CT scans for SARS-CoV-2 (COVID-19) identification created by our partners at Lancaster University, Plamenlancaster: Professor Plamen Angelov Centre Director Lira, & his researcher, Eduardo Soares PhD. The Magic Leap 1 COVID-19 Detection System 2020 uses Tensorflow 2, Raspberry Pi 4 & Magic Leap 1 to provide a spatial computing detection system. This project uses Magic Leap 1, TensorFlow, Unity & Raspberry Pi 4. Build your own free Magic Leap 1 COVID-19 Detection System.
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