Notice of RetractionA scheme of improved training in license plate character recognition

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

It utilizes back-propagation neural network (BPNN) as the recognition system tool. The identification is done by the back propagation neural network (BPNN). Moreover, we improve BPNN some limitation, such as slow learning speed in the training process, leading to partial minimum values that are difficult to converge, and the need to retrain an enormous volume of data whenever new training samples are added or deleted. The technologies and related models used for recognizing the license plates are clearly described and given to demonstrate the effectiveness of the proposed model. Experimental results show that our system can effectively recognize most license plates character, including 10 numbers and 26 alphabet characters. The recognition rate is 90%.