A Deep Learning Model of Dual-Stage License Plate Recognition Applicable to the Data Processing Industry

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td class="align_left" rowspan="2">Method</td><td class="align_center" colspan="3">PVLP</td><td class="align_center" rowspan="2">Avg. ACC (%)</td><td class="align_center" rowspan="2">FPS</td></tr><tr class="thead"><td class="align_center">FC (%)</td><td class="align_center">TS (%)</td><td class="align_center">RS (%)</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td class="align_left">DLPR</td><td class="align_center">99.19</td><td class="align_center">99.43</td><td class="align_center">94.06</td><td class="align_center">97.56</td><td class="align_center">&gt;21</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Average accuracy (Avg. ACC) and speed (FPS) of DLPR using the PVLP dataset for license plate recognition.</div>

Mathematical Problems in Engineering

tab4

Table 4

Table 4: A Deep Learning Model of Dual-Stage License Plate Recognition Applicable to the Data Processing Industry 