44 research outputs found

    Result of polyp activity prediction for the red <i>Paragorgia C</i><sub><i>r</i></sub> using our LSTM approach.

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    Plots A) and B) show the ground truth and the results for and , respectively. For better visibility, the original results are smoothed using a Gaussian filter with σ = 5. If no value is available for the next or previous hour, values in the smoothed curve are marked with an “x”. For details on the handling of missing data before smoothing see S7 Text.</p

    Data for figures.

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    Non-image data that were used to generate figures shown in the paper, if not already contained in S1–S3 Data. (XZ)</p

    LSTM prediction results and correlations for the blue <i>Paragorgia</i>.

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    LSTM prediction and evaluation results and correlations of LSTM input sensor data and polyp activity for the blue Paragorgia colony Cb. (PDF)</p

    Region size development of coral <i>C</i><sub><i>b</i></sub>.

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    The plot shows the region size development of Cb during time period Γ2 in the images recorded by stereo camera sensor K0. Coral sizes in images recorded from different camera angles are marked by different colors. Region Segmentation was done using U-Net f*. The lower threshold applied to remove false positive Cb regions is shown as a red line.</p

    Patch generation for polyp activity classification.

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    A description of the method used for generating image patches to be used as classification model input. (PDF)</p

    Hyperparameter selection for segmentation and classification models.

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    A description of the parameter selection scheme used for the segmentation and classification models. (PDF)</p

    Example patch classification result for <i>C</i><sub><i>r</i></sub> and <i>C</i><sub><i>b</i></sub>.

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    Frames of extracted patches are shown in dark yellow if the patch was classified as showing extended polyps, while edges of patches classified as showing retracted polyps are colored blue. Gamma correction with γ = 0.3 was applied to improve visibility of the corals. Patches were generated based on masks segmented by model f1. Patch classification was done using models g1,r and g1,b for Cr and Cb, respectively.</p
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