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Through Deep Learning, Innova's OCR5 Offers Accuracy and Efficiency in ALPR

OCR5 is a multi-country and multi-platform license plate recognition engine that offers you a very high success rate

With Innova, you can discover OCR5, the first ALPR solution based on Deep Learning. This multi-country and multi-platform license plate recognition engine offers you a very high success rate.

At Innova, we are in constant development and innovation, and therefore, immersed in the technological trends offered. We have developed OCR 5, ALPR technology for automatic reading and recognition of license plates based on deep learning algorithms that allow us to reach a success rate of up to 99.15% and a perfect adaptation to different license plate formats depending on the country.

Thanks to the rigor and functionality of this license plate reading technology, the effectiveness in the recognition and management of license plate characters are done with a minimum margin of error less than 0.09%, providing reliability in all access control and security systems required by parking management and companies.

Also, thanks to the technology used, qualitative advantages can be obtained when optimizing processes and improving the experience of the users. On the other hand, deep learning allows our OCR5 ALPR Technology to improve in time and effort different tasks & integration such as:

  • Countries' License Plates training in record time
  • Fastens up deploy of OCR´s Code into different platforms
  • Allows the quick improvement un user experience (#payperplate, #dynamicexit, etc.)

What is Deep Learning and How Does it Work?

Deep learning is a machine learning technique that teaches computers and or machines to do what is natural for humans. That is, they are neural network systems that allow automatic and natural learnings since it has technology that emulates and imitates the way in which a human brain processes information. A clear example of this technology is found in driverless vehicles, predictions in the economy sector, among others. Deep learning is the key to voice control on devices like phones, tablets, televisions, and hands-free speakers. There is no doubt that there is a wide field to cover in order to discover its different applications and incredible results.

When we talk about Deep learning we refer to a computer model that learns to carry out classification tasks directly from images, text or sound. This technology achieves recognition precision with maximum accuracy and efficiency, improving human performance. Models are trained using a large set of labeled data and neural network architectures that contain many layers.

Most deep learning methods use neural network architectures, so these models are known as deep neural networks. The term "deep" refers to the number of hidden layers in the neural network, reaching up to 150.

Deep learning models are empowered by using large tagged data sets and neural network architectures that learn the characteristics directly from the data without the need for manual extraction of data.

This intelligent model allows various applications in our daily routine, at Innova Systems Group we have developed an automatic license plate recognition technology based on Deep learning: OCR5.

 

This intelligent model allows various applications in our daily routine, at Innova Systems Group we have developed an automatic license plate recognition technology based on Deep learning: OCR5.

About Innova Systems Group 

Innova's mission is to provide solutions for access control and for the management of traffic based on innovative technologies such as the recognition of license plates. It is renowned due to its customer service quality, facilitating the personal and professional growth of its employees, encouraging reconciliation measures, a good work environment, equal opportunities, and generating solid and sustainable benefits. All of this, searching the common good of society through a policy of corporate social responsibility which helps and generates opportunities for the most disadvantaged, and taking care of the environment.

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