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Machine Learning (ML) and Artificial intelligence (AI) for Object Classification

AWARE for On-Road & ANTHEM for Off-Road Perception

AWARE and ANTHEM are based on Special Neural Network training process with core Development and Milestones consist of:

Training and Test Data creation

Using Sensor Fusion System to create training data Manual refinement of training data

Using the full RDM

Identification of location and object classification at the same time

Using Preprocessing steps

Improved accuracy by introduction of edge detection algorithm

Following Hybrid approach

Further improvement by implementing a hybrid approach using identified subsets of the RDM

Improving the results by incorporating meta information as inputs

Additional data like target angle, distance and velocity lead to further improvements

Reality Check – Optimization Phase

Optimization is needed to fit the algorithms into the data flow of the system and the physical limitations.


  • Reached 94% accuracy goal after optimizing for throughput by considerably reducing the algorithm complexity and manual labeling percentage

    • Pedestrians

    • Vehicles

    • Bicycles & motorcycles

    • Static objects



  • Adjust to limitation of available memory

  • Adapting to radar RDM



  • Limit the data required to identify objects

  • Identification speed keeps up with frame rate

Learn more about our
Real-Time Perception AI

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