Strategies for Exploiting Independent Cloud Implementations of Biometric Experts in Multibiometric Scenarios

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left">  Procedure </td><td align="center">  EER </td><td align="center">VER@0.1FAR </td><td align="center">VER@0.01FAR</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left">Product-rule </td><td align="center">  0.0066 </td><td align="center">  0.9866 </td><td align="center">  0.9733</td></tr><tr><td align="left">Sum-rule </td><td align="center">  0.0063 </td><td align="center">  0.9875 </td><td align="center">  0.9736</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Quantitative comparison of the fusion rules with learned parameter <svg height="7.9499998" id="M108" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 12.225 7.9499998" width="12.225" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> for both techniques)—training data.

Mathematical Problems in Engineering

tab4

Table 4

Table 4: Strategies for Exploiting Independent Cloud Implementations of Biometric Experts in Multibiometric Scenarios 