Taxa counts and observer agreements.

<p>The taxa with their human and gold standard label amounts. Gold standard labels are computed as the centroid of a group of closely neighbouring human labels of the same taxon. Only groups with 3 human labels were taken into account. The background labels were randomly distributed and were all used as gold labels. Additionally, the inter- and intra-observer agreements are given by average and standard deviation pone.0038179.g001.tif(std-dev.) for the five experts.</p

Classification performance by supporter.

<p>Given are the Sensitivity (SE) and Positive Predictive Value (PPV) for all taxa, compared to different supporter values <i>k</i> for the gold standard. While the SE is increasing with increasing supporter value, the PPV is performing inversely. This shows, that the automated detection is more likely to find objects with a high observer agreement.</p

The complete (semi-)automated detection process.

<p>Different transects with several thousand images are stored in the BIIGLE online platform (top left). These images can be accessed by experts via the WWW (bottom left). For this experiment, a subset of one transect (marked green on the upper left) was shown to five experts to create a manually labelled training set for a group of pre-defined taxa. Those manual labels were at first used to optimize an image pre-processing for illumination correction (top middle). Afterwards, high dimensional feature vectors were extracted at the label positions to gain a training and test set for SVM optimization (bottom middle). The trained SVMs were then applied pixel-wise to the full field of view, to obtain a confidence value for each pixel and taxon (top right). These confidence values were then post-processed into a classification map, where each pixel is assigned to one taxon which allows taxon counts per image. These taxon counts can then be plotted along the length of the transect (bottom right).</p

The combination of human labels to gold standard labels.

<p>The left image shows a small white sea anemone with two human labels (as circles) which is not enough to create a gold standard label as a supporter count of was required (see text for details). The image in the middle shows a <i>Kolga hyalina</i> labeled by experts and its resulting gold standard label in between (as a cross). The right image shows a <i>Bathycrinus carpenterii</i> with human labels for the crown (blue) as well as the stalk (yellow). Both human label cliques have supporter and thus two gold standard labels are created.</p

Illustration of the pre-processing.

<p>Image A is an original sample taken from the HAUSGARTEN IV transect. B - F show the effect of different kernel sizes <i>M</i> for the Gaussian filter. The kernel sizes are as follows: B: <i>M</i> = 11, C: <i>M</i> = 101, D: <i>M</i> = 701, E: <i>M</i> = 1101, F: <i>M</i> = 1401). The curves show the output of the cluster-indices, plotted against <i>M</i>. The first value (<i>M</i> = 0) represents the unfiltered image. The curves are as follows: blue: Chalinski-Harabasz, green: Index-I, yellow: Davies-Boudlin, pink: intra-cluster variance, red: inter-cluster variance. The bold, black line is the mean of the five measures. The cluster indices were normalized to the interval [0.1] and show a good correlation, supporting a reasonable selection of the value <i>M</i> = 701.</p

Training, test and validation performance.

<p>Given are the training, test and validation performance as measured by Sensitivity (SE) and Positive Predictive Value (PPV). The training and test performances are computed with a 4-fold cross validation on the training set. In the validation step, iSIS was applied to the entire images for taxa detection and the detection results were compared to our gold standard by computing SE and PPV. The performance decreases significantly from the test data to the validation due to an increase in FP. The last row shows SE and PPV results after a careful re-evaluation of the FP (see text for details) yielding our final estimates for iSIS’ SE and PPV. The last column shows the correlation between object counts of the gold standard items and the machine detection result for the full transect.</p

Map of the HAUSGARTEN Observatory.

<p>The main sampling station (HAUSGARTEN IV) is located at the intersection of the red lines.</p