<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>sibgrapi.sid.inpe.br 802</site>
		<holdercode>{ibi 8JMKD3MGPEW34M/46T9EHH}</holdercode>
		<identifier>8JMKD3MGPAW/3PFAFJL</identifier>
		<repository>sid.inpe.br/sibgrapi/2017/08.18.12.21</repository>
		<lastupdate>2017:08.18.12.21.50 sid.inpe.br/banon/2001/03.30.15.38 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/sibgrapi/2017/08.18.12.21.50</metadatarepository>
		<metadatalastupdate>2022:06.14.00.08.46 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2017}</metadatalastupdate>
		<doi>10.1109/SIBGRAPI.2017.14</doi>
		<citationkey>SilvaJung:2017:ReBrLi</citationkey>
		<title>Real-Time Brazilian License Plate Detection and Recognition Using Deep Convolutional Neural Networks</title>
		<format>On-line</format>
		<year>2017</year>
		<numberoffiles>1</numberoffiles>
		<size>2823 KiB</size>
		<author>Silva, Sergio Montazzolli,</author>
		<author>Jung, Claudio Rosito,</author>
		<editor>Torchelsen, Rafael Piccin,</editor>
		<editor>Nascimento, Erickson Rangel do,</editor>
		<editor>Panozzo, Daniele,</editor>
		<editor>Liu, Zicheng,</editor>
		<editor>Farias, Mylène,</editor>
		<editor>Viera, Thales,</editor>
		<editor>Sacht, Leonardo,</editor>
		<editor>Ferreira, Nivan,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Hirata, Nina,</editor>
		<editor>Schiavon Porto, Marcelo,</editor>
		<editor>Vital, Creto,</editor>
		<editor>Pagot, Christian Azambuja,</editor>
		<editor>Petronetto, Fabiano,</editor>
		<editor>Clua, Esteban,</editor>
		<editor>Cardeal, Flávio,</editor>
		<e-mailaddress>smsilva@inf.ufrgs.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 30 (SIBGRAPI)</conferencename>
		<conferencelocation>Niterói, RJ, Brazil</conferencelocation>
		<date>17-20 Oct. 2017</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>License Plate, Convolutional Neural Networks, Deep Learning.</keywords>
		<abstract>Automatic License Plate Recognition (ALPR) is an important task with many applications in Intelligent Transportation and Surveillance systems. As in other computer vision tasks, Deep Learning (DL) methods have been recently applied in the context of ALPR, focusing on country-specific plates, such as American or European, Chinese, Indian and Korean. However, either they are not a complete DL-ALPR pipeline, or they are commercial and utilize private datasets and lack detailed information. In this work, we proposed an end-to-end DL-ALPR system for Brazilian license plates based on state-of-the-art Convolutional Neural Network architectures. Using a publicly available dataset with Brazilian plates, the system was able to correctly detect and recognize all seven characters of a license plate in 63.18% of the test set, and 97.39% when considering at least five correct characters (partial match). Considering the segmentation and recognition of each character individually, we are able to segment 99% of the characters, and correctly recognize 93% of them.</abstract>
		<language>en</language>
		<targetfile>real-time-brazilian (3).pdf</targetfile>
		<usergroup>smsilva@inf.ufrgs.br</usergroup>
		<visibility>shown</visibility>
		<documentstage>not transferred</documentstage>
		<mirrorrepository>sid.inpe.br/banon/2001/03.30.15.38.24</mirrorrepository>
		<nexthigherunit>8JMKD3MGPAW/3PKCC58</nexthigherunit>
		<nexthigherunit>8JMKD3MGPEW34M/4742MCS</nexthigherunit>
		<citingitemlist>sid.inpe.br/sibgrapi/2017/09.12.13.04 5</citingitemlist>
		<citingitemlist>sid.inpe.br/sibgrapi/2022/06.10.21.49 2</citingitemlist>
		<hostcollection>sid.inpe.br/banon/2001/03.30.15.38</hostcollection>
		<agreement>agreement.html .htaccess .htaccess2</agreement>
		<lasthostcollection>sid.inpe.br/banon/2001/03.30.15.38</lasthostcollection>
		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi/2017/08.18.12.21</url>
	</metadata>
</metadatalist>