13 research outputs found
Automated plant species identification—Trends and future directions - Fig 3
<p>Visual variation of <i>Lapsana communis</i>'s flower throughout the day from two perspectives (left) and visual variation of <i>Centaurea pseudophrygia</i>'s flower throughout the season and flowering stage (right).</p
Overview of previously studied benchmark datasets.
<p>Overview of previously studied benchmark datasets.</p
Increasing classification accuracy achieved with evolving machine learning approaches on popular plant species benchmark datasets.
<p>Increasing classification accuracy achieved with evolving machine learning approaches on popular plant species benchmark datasets.</p
Results reported for the Oxford Flower 17 and Oxford Flower 102 datasets using local features along with the methods detailed for each processing step.
<p>Results reported for the Oxford Flower 17 and Oxford Flower 102 datasets using local features along with the methods detailed for each processing step.</p
Classification accuracy on the OF17, the OF102, and the JF30 dataset.
<p>Computed using SIFT in combination with the Hessian and Harris-based detectors without and with (values in brackets) affine shape estimation.</p
Challenging examples from the Jena Flower 30 (JF30) dataset.
<p>(a) and (b) Evolution of two flowers throughout the season and (c) Species with similar visual appearance: <i>Lotus corniculatus</i> vs. <i>Hippocrepsis comosa</i>, <i>Scabiosa columbaria</i> vs. <i>Knautia arvensis</i>, <i>Inula hirta</i> vs. <i>Inula salicina</i>.</p
Classification accuracies using (a) DoH-SIFT and (b) DoH-DCD features and different encoding methods for discrete codebook sizes and image representation lengths.
<p>Classification accuracies using (a) DoH-SIFT and (b) DoH-DCD features and different encoding methods for discrete codebook sizes and image representation lengths.</p
Class averaged classification accuracies for the fused shape and color descriptors on the OF17, the OF102, and the JF30 datasets all using the DoH detector.
<p>Class averaged classification accuracies for the fused shape and color descriptors on the OF17, the OF102, and the JF30 datasets all using the DoH detector.</p
Class averaged classification accuracies on the OF17, the OF102, and the JF30 datasets using DoH-OpponentSIFT and an increasing amount of pyramidal levels (one to three).
<p>Class averaged classification accuracies on the OF17, the OF102, and the JF30 datasets using DoH-OpponentSIFT and an increasing amount of pyramidal levels (one to three).</p
Median amount of local features extracted per image for the OF17, the OF102, and the JF30 dataset.
<p>Median amount of local features extracted per image for the OF17, the OF102, and the JF30 dataset.</p