YoVDO

Corona-Net

Offered By: EuroPython Conference via YouTube

Tags

EuroPython Courses Machine Learning Courses Image Segmentation Courses Classification Courses COVID-19 Courses U-Net Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore an open-source project dedicated to combating COVID-19 through machine learning in this EuroPython 2020 conference talk. Dive into Corona-Net, a three-part initiative focusing on classification, binary segmentation, and multi-class segmentation of COVID-19 using chest CT scans. Learn about the implementation of EfficientNet for diagnosis and the refinement of U-Net architecture for symptom segmentation. Discover how this project aims to develop a reliable, visually-semantically balanced method for automatic COVID-19 diagnosis while inviting collaboration in the global fight against the pandemic. Gain insights into the project's background, problem statement, model architecture, classification techniques, fully convolutional networks, and future development plans.

Syllabus

Intro
Self Intro
Background
Problem Statement
Model Architecture
Classification
Fully Convolutional Networks
Future Development


Taught by

EuroPython Conference

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Natural Language Processing
Columbia University via Coursera
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent