Capsule Network-based Framework for Identification of COVID Cases from X-ray Images
Offered By: Toronto Machine Learning Series (TMLS) via YouTube
Course Description
Overview
Explore a cutting-edge modeling framework based on Capsule Networks, known as COVID-CAPS, designed to identify COVID-19 cases from X-ray images. In this 20-minute conference talk presented at the Toronto Machine Learning Series (TMLS), learn how this innovative approach effectively handles small datasets, a crucial advantage given the sudden and rapid emergence of COVID-19. Discover the advantages of COVID-CAPS over previous CNN-based models and gain insights into its performance using X-ray image datasets. Delve into the potential of Capsule Networks in medical imaging and their application in addressing urgent healthcare challenges.
Syllabus
Parnian Afshar - Capsule Network-based Framework for Identification of COVID cases from X-ray Images
Taught by
Toronto Machine Learning Series (TMLS)
Related Courses
Perioperative Medicine in ActionUniversity College London via FutureLearn Tackling Antimicrobial Resistance: A Social Science Approach
Imperial College London via FutureLearn Vaccines and COVID-19 Teach-Out
University of Michigan via Coursera COVID-19: Tackling the Novel Coronavirus
London School of Hygiene & Tropical Medicine via FutureLearn Science Matters: Let's Talk About COVID-19
Imperial College London via Coursera