Automotive

The role of AI in the Automotive Industry has become crucial in the present and will be inevitable in the future. ML Data Ocean has a collection of a variety of datasets in large amounts that will help you become a part of the advanced future.

Top AI Use cases in Automotive Industry

Partial or Fully Autonomous Vehicles

Train your self-driving models with a wide range of road datasets that help improve learning models' reasoning power and causal understanding. With our annotations increase your learning model's accuracy.

Polygon

Manufacturing Equipment

Revolutionize the way of manufacturing vehicles by using AI-powered robots to build custom cars and also minimize human need in assembling parts.

Vehicle Design and Testing

Save the time and cost of designing vehicles by computer modelling. Test vehicles before building a physical model by training them in a simulation with realistic scenarios.

Polygon

Quality Control

Train your self-driving models with a wide range of road datasets that help improve learning models' reasoning power and causal understanding. With our annotations increase your learning model's accuracy.

Annotation in Automotive

Image by Hal Gatewood

3D Cuboids

Image by Hal Gatewood

Polygon

Image by Hal Gatewood

Semantic Segmentation

Image by Hal Gatewood

Lines and Splines

Benefits

Image by Hal Gatewood

Improve User Experience

Ensure safe driving with a reduction of malfunction in vehicles. Driverless cars to reduce road accidents due to human errors.

Image by Philip Strong

Enhance Manufacturing and Maintenance

Minimize the time of manufacturing along with saving the cost of production. Prediction of malfunction helps in the maintenance of vehicles.

Image by Petrebels

Faster Innovation Cycles

With computer vision, original equipment manufacturers can create safer and innovative vehicles with faster production helping them in the long run.