Deep Learning for feature extraction from point clouds

15:45-16:05, January 28 @ 1BC

Talk/ Overview

LiDAR sensors are an important and reach source of high-precision 3D point clouds, which are quite useful in modern urban design and planning. Such point clouds are easy to collect but slow and expensive to segment into classes and individual objects. We are going to talk about various applications of common deep neural networks in segmenting and labeling point clouds for fast reconstruction of 3D building models at scale, detection of overhead conductors and utility poles, street furniture etc.

Talk/ Speakers

Dmitry Kudinov

Senior Principal Data Scientist

Talk/ Slides

Download the slides for this talk.Download ( PDF, 88973.45 MB)

Talk/ Highlights

20:58

Deep Learning for feature extraction from point clouds

With Dmitry KudinovPublished March 11, 2020

AMLD / Global partners