Scale AI
Case Studies
Velodyne's Use of Scale Nucleus for Efficient Data Annotation in 3D Lidar Technology
Overview
Velodyne's Use of Scale Nucleus for Efficient Data Annotation in 3D Lidar TechnologyScale AI |
Sensors - Autonomous Driving Sensors Sensors - Lidar & Lazer Scanners | |
Automotive E-Commerce | |
Warehouse & Inventory Management | |
Object Detection Virtual Prototyping & Product Testing | |
Cloud Planning, Design & Implementation Services Training | |
Operational Impact
With the implementation of Scale Nucleus, Velodyne's data team is now able to efficiently curate new datasets. The time taken to curate a 3D lidar dataset has been significantly reduced from days or even weeks to just a few hours. This has allowed the team to quickly identify new edge cases that their models are struggling with and refine ground truth as their library grows. More broadly, Velodyne's customers are using their lidar-equipped robotics for accurate object detection, classification, and path estimation, enabling them to move goods with a high level of precision, efficiency, and safety, and helping to maintain continuity of operations. | |
Quantitative Benefit
Nucleus reduced training data selection times for the data team by 50%. | |
The Velodyne team was able to drill down on edge cases in a matter of hours, reducing the dataset creation step and kicking off their annotation job days earlier. | |