Hayden Ai Technologies, Inc.

Hayden Al Technologies, Inc.

Morgan Kohler

Bo Shen

Vaibhav Ghadiok

Shaocheng Wang

Andrei Liaukovich

Maciej Budys

Marcin Grzesiak

Wiktor Muron

Michael Gleeson-May

Disclosed herein are methods, systems, and apparatus for automated license plate recognition and methods for training a machine learning model to undertake automated license plate recognition. For example, a method can comprise dividing an image or video frame comprising a license plate into a plurality of image patches, determining a positional vector for each of the image patches, adding the positional vector to each of the image patches and inputting the image patches and their associated positional vectors to a text-adapted vision transformer. The text-adapted vision transformer can be configured to output a prediction concerning the license plate number of the license plate.

Systems and methods for automated license plate recognition

Disclosed herein are methods and systems for automatically validating evidence of traffic violations. One instance of a method comprises receiving an evidence package comprising video frames showing a vehicle involved in a potential traffic violation. The video frames can be input into one or more deep learning models to obtain a plurality of classification results. The method can further comprise generating a score based in part on the classification results and evaluating the score against one or more thresholds to determine whether the evidence package is automatically approved, is automatically rejected, or requires further review.

System and methods for automatically validating evidence of traffic violations using automatically detected context features

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Mill Valley, CA, United States of America

Morgan Kohler