Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education

<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">Model</td><td class="align_center">Accuracy of model (%)</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Yolov4 for equation</td><td class="align_center">96</td></tr><tr><td class="align_left">Yolov4 for character</td><td class="align_center">95</td></tr><tr><td class="align_left">VGG-16</td><td class="align_center">98</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Comparing accuracy of model after training.</div>

Applied Computational Intelligence and Soft Computing

tab3

Table 3

Table 3: Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education 