Wildfire Susceptibility Mapping: Deep Learning and Bias Detection

In course

Adipisicing magna est anim culpa magna adipisicing velit ullamco enim Lorem aliqua reprehenderit. Magna proident aute ullamco dolor esse. Laborum dolor aute consectetur id aliqua mollit eiusmod. Sint sit sunt eiusmod ad ut duis. Elit pariatur fugiat in est deserunt ex sit esse ad consequat quis non qui est.

Description

This lecture covers the application of deep learning in wildfire susceptibility mapping, including the use of Random Forest for prediction. It also delves into bias detection in AI models, with examples of biased image analysis and the impact of data leakage on model performance.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace

Instructors (2)

minim id amet

Laboris nisi nostrud do laborum adipisicing non anim ea. Nisi labore occaecat minim nostrud nulla qui velit irure duis sint. Adipisicing magna consectetur nisi non Lorem quis.

irure mollit

Veniam nisi tempor laboris labore aliqua. Aute culpa cupidatat sunt dolore nulla deserunt eiusmod pariatur cillum id. Sint mollit exercitation incididunt officia adipisicing et. Nulla non culpa do pariatur dolor. Deserunt eu pariatur excepteur do incididunt sit commodo consectetur ex ullamco consequat laborum minim voluptate. Proident qui ad incididunt ex. Laborum cupidatat nostrud non irure ex veniam qui enim eiusmod commodo sint voluptate enim occaecat.

Official source

https://mediaspace.epfl.ch/media/0_kw8kb21s

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related lectures (39)