Nonnegative Matrix Factorizations Performing Object Detection and Localization

<table>Behavior of the MSE during the learning iterations for the CarData dataset ((a) rank value <svg height="10.9125" id="M207" style="vertical-align:-0.17555pt" version="1.1" viewbox="0 0 41.512501 10.9125" width="41.512501" xmlns="http://www.w3.org/2000/svg">
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<tspan style="font-size: 12.50px; " x="0" y="0">𝑟</tspan>
<tspan style="font-size: 12.50px; " x="8.5645552" y="0">=</tspan>
<tspan style="font-size: 12.50px; " x="20.604944" y="0">2</tspan>
<tspan style="font-size: 12.50px; " x="26.856443" y="0">0</tspan>
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</svg>, (b) rank value <svg height="11.1" id="M208" style="vertical-align:-0.17555pt" version="1.1" viewbox="0 0 49.337502 11.1" width="49.337502" xmlns="http://www.w3.org/2000/svg">
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<g transform="translate(72,-63.12)">
<text transform="matrix(1,0,0,-1,-71.95,63.35)">
<tspan style="font-size: 12.50px; " x="0" y="0">𝑟</tspan>
<tspan style="font-size: 12.50px; " x="8.5645552" y="0">=</tspan>
<tspan style="font-size: 12.50px; " x="20.604944" y="0">1</tspan>
<tspan style="font-size: 12.50px; " x="26.856443" y="0">1</tspan>
<tspan style="font-size: 12.50px; " x="33.107944" y="0">5</tspan>
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</svg>).</table>

Applied Computational Intelligence and Soft Computing

fig8

Figure 8

Figure 8: Nonnegative Matrix Factorizations Performing Object Detection and Localization 