Inspection Technology of Power Communication Network Based on Machine Vision Graphic Recognition

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left">Category</td><td class="align_center">Accuracy rate (%)</td><td class="align_center">False detection rate (%)</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">CNN</td><td class="align_center">76</td><td class="align_center">6</td></tr><tr><td class="align_left">RPN + Fast R-CNN</td><td class="align_center">85.5</td><td class="align_center">1.5</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Seven types of electrical equipment identification results.</div>

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Table 3

Table 3: Inspection Technology of Power Communication Network Based on Machine Vision Graphic Recognition 