Recognition Method of Tunnel Lining Defects Based on Deep Learning

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Network</td><td class="align_center">Number of parameters</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">ResNet34</td><td class="align_center">21,285,698</td></tr><tr><td class="align_left">Improved ResNet34</td><td class="align_center">20,386,626</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Parameters of different models.</div>

Wireless Communications and Mobile Computing

tab4

Table 4

Table 4: Recognition Method of Tunnel Lining Defects Based on Deep Learning 