aiMotive at AutoSens Detroit 2022

Let's meet there!

Responsive Image

Don’t miss out on a chance to learn more about the world’s most advanced data pipeline for automated driving by aiMotive; meet us for a private discussion at booth 43. We will also introduce our market-ready, end-to-end products and give you a sneak peek of our latest cutting-edge, industry-leading solutions. If you are attending AutoSens Detroit 2022, reach out to us and let's set up an in-person discussion.

Contact Us
Responsive Image

Don't miss our keynote

Synthetic Data and Automatic Annotation for Training and Validating Next-Generation Automated Driving Solutions

by Dr. Peter Kovacs, Production SVP, aiMotive

WEDNESDAY 11 MAY 2022, 4:40 PM

 

Check out our latest stories

News, blogposts & more about aiMotive

Asset Publisher

5 October 2022

Synthetic data generation – beating the data challenge of automated driving

Data is critical to neural network (NN) development. Automatic annotation is the most effective and cheapest way to generate training and validation data from real-world recordings. But what about hard-to-capture scenarios or corner cases that hardly ever occur in real life? Automated driving systems still need to be aware of such events.

Read More

23 September 2022

aiMotive paper to be presented at a scientific conference in Vietnam

The paper titled 'A Novel Neural Network Training Method for Autonomous Driving Using Semi-Pseudo-Labels and 3D Data Augmentations' written by Tamás Matuszka and Dániel Kozma has been accepted to the 14th Asian Conference on Intelligent Information and Database Systems (Category B in the 2021 CORE conference rankings) and will be published in Springer's Lecture Notes in Artificial Intelligence. The work will be presented in Ho Chi Minh City, Vietnam, on November 28-30, 2022.

Read More

25 August 2022

Auto annotation: cost-efficient, fast and adaptive

Annotation is the most expensive element of training data generation, so truly automatic annotation remains the holy grail of automated driving development – aside from the ability to generate synthetic data that is indistinguishable from real data.

Read More