GSoC 2020 with LibreHealth : Final Report
Low Powered Models for Disease Detection and Classification for Radiology Images Project Description - The aim of this project is to create Deep Learning models for detection and classification of radiology images. The models must be compressed such that they can be deployed to low powered devices like ARM devices, Android devices, etc. Compression techniques such as Quantization and Pruning can be used. Mentors - Priyanshu Sinha Saptarshi Purkayastha Judy Gichoya Geeta Priya Padmanabhan Tech Stack - Numpy Pandas PyDicom Tensorflow Tensorflow-Lite/ Tensorflow-Model-Optimization Docker Qemu Project Link - Click here Commits - Click here Merge Requests - Click here Why to do this - There has been a lot of progress in developing Machine Learning models that predict the medical condition of a patient based upon specific inputs relevant to the diagnosis of that condition. However, these models have drawbacks while deployment in real-time on edge devices. Firstly, they have been trai