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Application example
In automobile production, different vehicle variants are manufactured on one and the same production line. In order to ensure that the correct type of tank nozzle has been installed in the correct vehicle, a vision sensor should carry out a type check.
Identifiying reliable distinguishing features is crucial for the vision sensor to differentiate between various types of fuel filler necks. However, using traditional, rule-based methods can be time-consuming and my have limitations. Moreover, detecting the compnents´ reflections can further increase the difficulty of detection.
The robust vision sensor with artificial intelligence VISOR® Object AI enables a reliable distinction to be made between the different fuel filler neck types. By assigning a few sample images to each class, the Classification (AI) detector automatically learns to distinguish between the different types – no expert knowledge is required to set it up. Position variations and reflections can be taught to the detector and it will learn the necessary features. The vision sensor offers a robust and reliable solution for the type control of fuel filler necks in cars.
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