A Robust Approach for Licence Plate Detection Using Deep Learning

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<title>A Robust Approach for Licence Plate Detection Using Deep Learning</title>
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<namePart>Arora, Shefali</namePart>
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<abstract displayLabel="Summary">Intelligent transport systems must be developed due to the rising use of vehicles, particularly cars. In the field of computer vision, the identification of a vehicle's licence plate (LP) has been crucial. Various methods and algorithms have been used for the detection process. It becomes challenging to find similar photos, nevertheless, because the features of these plates change depending on colour, font, and language of characters. The research proposes a powerful deep learning framework based on feature extraction using convolutional neural networks and localization using canny-edge detection</abstract>
<note type="statement of responsibility">Shefali Arora [et al.]</note>
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<topic>Vehículos</topic>
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<topic>Sistemas de transporte inteligentes</topic>
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<topic>Matrículas</topic>
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<topic>Automóviles</topic>
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<topic>Inteligencia artificial</topic>
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<url displayLabel="electronic resource" usage="primary display">https://journal.iberamia.org/index.php/intartif/article/view/1107</url>
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<title>Revista Iberoamericana de Inteligencia Artificial</title>
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<publisher> : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</publisher>
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<identifier type="issn">1988-3064</identifier>
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<text>19/06/2024 Volumen 27 Número 73 - junio 2024 , p. 129-141</text>
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