A modular neural network classifier for the recognition of occluded characters in automatic license plate reading
Occlusion is the most common reason for lowered recognition yield in free-flow license-plate reading systems. (Non-)occluded characters can readily be learned in separate neural networks but not together. Even a small proportion of occluded characters in the training set will already significantly reduce the overall recognition yield. This paper shows that a modular network can handle a realistic
