Fast LIDAR processing & Classification – 18 GB approx 9 hours by regular PC
Highly accurate (+/- 5-10 cm) mapping & 80-90% accuracy of Classification
Compressed data model size – 1/10th of regular size
Rich experience in mapping with LIDAR and imagery
Cool add-ons to make LIDAR data processing compelling
Highly effective automation process
Rapid processing of LIDAR (Airborne, Mobile, etc.) data into 3d imagery
Visionary, market oriented and driven
AI - Classification
Fully automatic separation of non-ground from ground points
Automatic detection and classification of LIDAR points into buildings, trees, vegetation, traffic signs, light poles and many other objects through our deep learning capabilities.
Collecting large amounts of data is important for both testing and situation analysis as well as supplying the training data needs of deep learning. YADO-VR and the way it has been build, complimented with powerful algorithms, is able to process large amounts of LIDAR generated point cloud data. The data collection is part of the Yado-VR base platform.
The Deep Learning capabilities of YADO-VR fuses all the essential data to accelerate the training and verification of the data gathered from sensor technology.. The Yado-VR ecosystem has all the functions to provide an automated DETECTION and automated CLASSIFICATION environment, making sure you end up with usable computer vision output to make the right decisions.
Relevant objects on the collected data have to be labeled precisely in order for the AI platform to learn all the classes reliably. The annotation and classifications functions makes multisensor data annotation many times faster than the manual method.