The existing license plate recognition system is unable to locate accurately in the cases of complex background and license plate tilting. To solve this issue, this study proposes an end-to-end license plate location algorithm based on a convolutional neural network to accurately calculate the license plate coordinates. The information is extracted based on the input vehicle picture using Faster R-CNN to obtain the feature mapping of the candidate area. Further, the license plate coordinates are precisely obtained using feature mapping. The experimental results denote that the recognition accuracy of the proposed algorithm is 99% with respect to the functional assessment database of the OpenITS database and 85% with respect to the performance evaluation database.