Arpitha U's Projects
365 Days Computer Vision Learning Linkedin Post
Evaluating the association between blood group and COVID-19
Description PoC for the 2020 WirVSVirus Hackathon
An Optimized TL-based Approach for Auto. Detection of COVID-19 from Chest X-ray Images
A tool which helps in identifying COVID-19 patients using their X-ray images using Classification and Segmentation Techniques
A curated list of automated machine learning papers, articles, tutorials, slides and projects
Valencia Region Image Bank (BIMCV) that combines data from the PadChest dataset with future datasets based on COVID-19 pathology to provide the open scientific community with data of clinical-scientific value that helps early detection of COVID-19
The Microsoft Bot Framework provides what you need to build and connect intelligent bots that interact naturally wherever your users are talking, from text/sms to Skype, Slack, Office 365 mail and other popular services.
Investigate the performance of classification algorithms to select the appropriate classification algorithm for the "Breast Cancer Coimbra" data set.
End-to-end learning for semiquantitative rating of COVID-19 severity on Chest X-rays. Additional material and updates.
This repo is for the Linkedin Learning course: C# Advanced Object-Oriented Programming
C#: Delegates, Events and Lambdas
C#: Interfaces and Generics
A collection of CCL source code for executing CCL Unit tests and generating code coverage data.
Implementation of https://arxiv.org/abs/2003.08592
A TensorFlow project that has allowed me to create a machine learning classifying program to identify thoracic diseases (diseases that have been identified by radiologists)
Experimental Notebook and Script components ready to be dropped in an Elyra pipeline
Semantics for COVID-19 Discovery
It is a Flask Application to predict a person covid positive/negetive based on chest x ray of a person.This Machine Learning Web Application utilizes a Two-Layered Convolutional Neural Network to process the chest-x-ray Images and predict if they are corona positive/negetive accuracy of nearly 81%.
Diagnosis of corona virus using Chest X-ray and CT-scan through deep learning
Jupyter notebooks and python scripts for investigating the 2019 coronavirus outbreak
The COVID-19 Early Warning System (CovEWS) is a real-time early warning system for assessing individual COVID-19 related mortality risk.
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
A team of researchers from Qatar University, Doha, Qatar and the University of Dhaka, Bangladesh along with their collaborators from Pakistan and Malaysia in collaboration with medical doctors have managed to classify COVID-19, Viral pneumonia and Normal Chest X-ray images with an accuracy of 98.3%. This scholarly work is submitted to Scientific Reports (Nature) and the manuscript is uploaded to the arvix server(https://arxiv.org/abs/2003.13145). Please make sure you give credit to us while using this repository(https://github.com/tawsifur/COVID-19-Chest-X-ray-Detection) and this database( https://www.kaggle.com/tawsifurrahman/covid19-radiography-database)
Community effort to build a Neo4j Knowledge Graph (KG) that links heterogeneous data about COVID-19
Covid-19 Detection Experiments
COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can upload Chest X-rays or CT Scans and get the output of possibility of COVID infection.