DCCAM-MRNet: Mixed Residual Connection Network with Dilated Convolution and Coordinate Attention Mechanism for Tomato Disease Identification

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Network model</td><td class="align_center">Accuracy (%)</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">ResNeXt50</td><td class="align_center">86.6</td></tr><tr><td class="align_left">ResNeXt50-SE</td><td class="align_center">87.5</td></tr><tr><td class="align_left">ResNeXt50-CMBA</td><td class="align_center">88.9</td></tr><tr><td class="align_left">ResNeXt50-CA</td><td class="align_center">90.2</td></tr><tr><td class="align_left">DCCAM-MRNet</td><td class="align_center">94.3</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The influence of coordinate attention on network accuracy.</div>

Computational Intelligence and Neuroscience

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Table 3

Table 3: DCCAM-MRNet: Mixed Residual Connection Network with Dilated Convolution and Coordinate Attention Mechanism for Tomato Disease Identification 

Table 3 | DCCAM-MRNet: Mixed Residual Connection Network with Dilated Convolution and Coordinate Attention Mechanism for Tomato Disease Identification 