YoVDO

Chan Vese Attention U-Net - An Attention Mechanism for Robust Segmentation

Offered By: Conference GSI via YouTube

Tags

Image Segmentation Courses Deep Learning Courses Computer Vision Courses Medical Imaging Courses Attention Mechanisms Courses U-Net Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore an innovative attention mechanism for robust segmentation in this 20-minute conference talk from GSI. Learn about the Chan Vese Attention U-Net, a novel approach that enhances segmentation accuracy and reliability across various applications. Discover how this advanced technique combines the strengths of the Chan-Vese model with attention mechanisms to improve U-Net performance. Gain insights into the architecture, implementation, and potential benefits of this cutting-edge segmentation method for computer vision and image processing tasks.

Syllabus

Chan Vese Attention U-Net: An attention mechanism for robust segmentation


Taught by

Conference GSI

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera
機器學習技法 (Machine Learning Techniques)
National Taiwan University via Coursera
Machine Learning Capstone: An Intelligent Application with Deep Learning
University of Washington via Coursera
Прикладные задачи анализа данных
Moscow Institute of Physics and Technology via Coursera
Leading Ambitious Teaching and Learning
Microsoft via edX