Character level vehicle license detection using multi layered feed forward back propagation neural network

Real-world traffic situations, including smart monitoring, automated parking systems, and car services are increasingly using vehicle license detection systems (VLDS). Vehicle plate identification is still a challenge with current approaches, particularly in more complicated settings. The use of machine learning deep algorithms, which display improved classification accuracy resilience, has been significant recent breakthrough. Deep learning-based neural networks proposed this article. number detected multi layered feed forward back propagation network (MLFFBPNN). In method, there 3 layers namely input, hidden, output utilized. Each layer related interconnection weights. information, initially set randomly chosen weights to the input data an determined. Back training algorithm utilized train network. Then character level performed. suggested method compared region-based convolutional (RCNN) terms computational efficiency. produced recognition 89%. It by 4% when RCNN method.