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A Robust Approach for Licence Plate Detection Using Deep Learning

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      <subfield code="a">A Robust Approach for Licence Plate Detection Using Deep Learning</subfield>
      <subfield code="c">Shefali Arora [et al.]</subfield>
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      <subfield code="a">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</subfield>
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      <subfield code="0">MAPA20080552916</subfield>
      <subfield code="a">Vehículos</subfield>
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      <subfield code="0">MAPA20080643874</subfield>
      <subfield code="a">Sistemas de transporte inteligentes</subfield>
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      <subfield code="0">MAPA20080555108</subfield>
      <subfield code="a">Matrículas</subfield>
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    <datafield tag="650" ind1=" " ind2="4">
      <subfield code="0">MAPA20080557287</subfield>
      <subfield code="a">Automóviles</subfield>
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      <subfield code="0">MAPA20080611200</subfield>
      <subfield code="a">Inteligencia artificial</subfield>
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      <subfield code="0">MAPA20240020866</subfield>
      <subfield code="a">Arora, Shefali</subfield>
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      <subfield code="g">19/06/2024 Volumen 27 Número 73 - junio 2024 , p. 129-141</subfield>
      <subfield code="x">1988-3064</subfield>
      <subfield code="t">Revista Iberoamericana de Inteligencia Artificial</subfield>
      <subfield code="d"> : IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</subfield>
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      <subfield code="u">https://journal.iberamia.org/index.php/intartif/article/view/1107</subfield>
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