Q-Free developing new machine learning tech for ALPR

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Q-Free has announced it is developing improved vehicle analytics and detection for its automatic license plate recognition (ALPR/ANPR) technology that identifies vehicle class, colour, make/model (MMR), and which side of the vehicle is being analyzed.

The vehicle analytics feature is an extension of the company’s Intrada ALPR which processes more than a billion license plates around the globe each day. As a vendor-agnostic solution, Q-Free sees this as a convenient extension that opens new possibilities for its customers’ operations and business models without the need to change their existing video infrastructure or invest in costly hardware-based alternatives such as radar and laser.

Data from test sites in South America and Asia show surveillance and security operators successfully gathering additional identifying characteristics leveraging existing video detection equipment.

The new vehicle analytics are a result of innovative, reliable neural networks and the company’s machine learning capabilities according to Marco Sinnema, product manager for Q-Free’s Intrada ALPR library. “Work with initial customers continues to train the detection of the neural networks – which is now available in our commercial, off-the-shelf Intrada ALPR library,” he says. “Early results are showing the system performing with great precision, and we plan on delivering the same unrivalled automation accuracy and low error rates offered in our existing ALPR solutions.”

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Tom has edited Traffic Technology International magazine and the Traffic Technology Today website since May 2014. During his time at the title he has interviewed some of the top transportation chiefs in charge of public agencies around the world as well as chairmen and CEOs of multinational transportation technology corporations. Tom's early career saw him working on some the UK's leading consumer magazine titles. He has a law degree from the London School of Economics (LSE).