Deep Learning Approach for Estimating Workability of Self-Compacting Concrete from Mixing Image Sequences

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">R</td><td class="align_center">Lengths of sequences</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">3</td><td class="align_center">11</td></tr><tr><td class="align_left">5</td><td class="align_center">7</td></tr><tr><td class="align_left">7</td><td class="align_center">5</td></tr><tr><td class="align_left">9</td><td class="align_center">3</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Time resolutions (<i>R</i>) and lengths of corresponding downsampling sequences.</div>

Advances in Materials Science and Engineering

tab5

Table 5

Table 5: Deep Learning Approach for Estimating Workability of Self-Compacting Concrete from Mixing Image Sequences 