چکیده مقاله
Employing deep learning approaches has resulted in magnificent perfections in computer vision applications in recent years In addition, Deep Neural Networks DNNs have shown to be remarkable alternatives for common shallow machine learning techniques like Support Vector Machines SVM Deep learning provides great solutions for both classic and modern image processing, feature extraction and object detection problems Considering the advantages of utilizing DNNs in a wide range of computer vision fields, this paper presents a concise review of different deep learning approaches employed in Automatic License Plate Recognition ALPR systems In such systems, deep learning techniques have been utilized in various phases of ALPR including license plate detection, character segmentation and Optical Character Recognition OCR Additionally, a comprehensive overview of common DNN architectures is introduced for better clarification and classification of introduced methods
کلیدواژهها
نویسندگان
Sajjad Soroori
Department of Computer Engineering, University of Guilan, Rasht, Iran
Ali Tourani
Department of Computer Engineering, University of Guilan, Rasht, Iran
Asadollah Shahbahrami
Department of Computer Engineering, University of Guilan, Rasht, Iran
شیوه ارجاع
Soroori, Sajjad and Tourani, Ali and Shahbahrami, Asadollah,1398,Employing Deep Learning Approaches for Automatic License Plate Recognition: A Review,3rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی محاسبات نرم29 آبان 1398 · رودسر