Method of real time vehicle recognition with neuromorphic computing network for autonomous driving

A computer implemented method for online vehicle recognition in an autonomous driving environment, the method comprising an act of:

• causing one or more processers to execute instructions encoded on a non-transitory computer-readable medium, such that upon execution, the one or more processors perform operations of:
• using a learning network comprising an unsupervised learning component and a supervised learning component, learning and classifying images of moving vehicles extracted from videos captured in the autonomous driving environment by:
• extracting vehicle feature data from input moving vehicle images;
• automatically clustering the extracted vehicle feature data into different vehicle classes using the unsupervised learning component;
• and
• generating vehicle class labels for the different vehicle classes using the supervised learning component;
• and
• selecting an action to be performed by an autonomous vehicle based on a vehicle class label for one or more moving vehicles in the autonomous driving environment;
• and
• causing the selected action to be performed by the autonomous vehicle in the autonomous driving environment.

A computer program product for online vehicle recognition in an autonomous driving environment, the computer program product comprising:

• computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having one or more processors for causing the processor to perform operations of:
• using a learning network comprising an unsupervised learning component and a supervised learning component, learning and classifying images of moving vehicles extracted from videos captured in the autonomous driving environment by:
• extracting vehicle feature data from input moving vehicle images;
• automatically clustering the extracted vehicle feature data into different vehicle classes using the unsupervised learning component;
• and
• generating vehicle class labels for the different vehicle classes using the supervised learning component;
• and
• selecting an action to be performed by an autonomous vehicle based on a vehicle class label for one or more moving vehicles in the autonomous driving environment;
• and
• causing the selected action to be performed by the autonomous vehicle in the autonomous driving environment.