Experiments show that LPR-SSD achieved a faster convergence speed during training. After the test set verification, the accuracy of license plate location detection and classification reaches 98.3%, and the character recognition accuracy rate reaches 99.1%.
Oct 22, 2024
Experiments show that the proposed method can more efficiently extract license plate features and effectively improve the license plate detection rate.
In this paper, the target detection algorithm is used to deeply study the license plate detection technology. Based on the SSD algorithm, the residual network ...
Experiments show that the proposed method can more efficiently extract license plate features and effectively improve the license plate detection rate.
It can be seen from Fig. 2 that the upper layer of the network architecture adopts an SSD-based object detection algorithm, and a new feature extraction layer ...
In order to improve the real time and precision of license plate detection in the license plate recognition system, this paper presents an improved license ...
This work proposes and demonstrates implementation of a deep learning-based approach to locate license plates of four wheeler vehicles thereby enabling ...
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This paper uses the method based on deep learning to detect and recognize the license plate. Due to the multi-scale detection ability of SSD target detection ...
License plate recognition in natural environments faces multiple challenges, including variations in shooting distance, tilt angle, light intensity, weather ...
May 22, 2023 · The application uses MobileNet Single Shot Detector (SSD) algorithm to read license plate and query for vehicles' information from Firebase ...