Application of Deep Learning in Integrated Pest Management: A Real-Time System for Detection and Diagnosis of Oilseed Rape Pests

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Method</td><td class="align_center">Accuracy</td><td class="align_center">Missing rate</td><td class="align_center">False reject rate</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Oilseed rape pest detection system</td><td class="align_center">0.6982</td><td class="align_center">0.2074</td><td class="align_center">0.0944</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>The test results of the mobile application.</div>

Mobile Information Systems

tab7

Table 7

Table 7: Application of Deep Learning in Integrated Pest Management: A Real-Time System for Detection and Diagnosis of Oilseed Rape Pests 