Powered by OpenAIRE graph
Found an issue? Give us feedback
ZENODOarrow_drop_down
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
addClaim

SWDD: Sonar Wall Detection Dataset

Authors: Aubard, Martin; Antal, László; Madureira, Maria; Ábrahám, Erika;

SWDD: Sonar Wall Detection Dataset

Abstract

The dataset SWDD: Sonar Wall Detection Dataset is part of the paper Knowledge Distillation in YOLOX-ViT for Side Scan Sonar Object Detection. SWDD has been recorded with a lightweight autonomous underwater vehicle (LAUV), operated by OceanScan-MST and carrying a Klein 3500 side scan sonar (SSS). The AUV has been deployed in the Porto de Leixões harbor following the harbor's walls while collecting SSS raw data. The SSS operated at a high frequency of 900kHz with a range of 75m for a total range of 150m from port to starboard. This setup produced a resolution of 4.168 pixels per line. The data were processed using Neptus software, transforming the raw data into waterfall images. The 216 images have been manually annotated with two different classes, wall and noWall. Data augmentation such as noise, flips, and combined noise-flip transformations have been applied, increasing the data to 864 images. Across the 864 images, there are a total of 2,616 labeled samples. To ensure robust training, with respect to the data quality, the original dataset has been mixed with the augmented images. The dataset is divided into 70% for training, 15% for validation, and 15% for testing. The authors chose to generate images with 500 lines, meaning the images have a resolution of 4.168x500. Finally, the images have been resized to 640 × 640 to use this data in specific computer vision algorithms. The dataset is annotated following the COCO annotation format. YOLOX and YOLOX-ViT have been trained and compared using the SWDD dataset. A 6-minute 57-second video from another survey was used for model comparison. From this video, 6243 frames have been extracted with its manually annotated ground truth. Thus, this dataset repository offers an SSS dataset, a 6-minute 57-second SSS video, and 6243 extracted frames from this video with its manually annotated ground truth. The Knowledge Distillation in YOLOX-ViT code using the SWDD dataset is publicly available at KD-YOLOX-ViT. For (re-)using/publishing SWDD, please include the following copyright text: SWDD is a public dataset collected with a Light Autonomous Underwater Vehicle by Oceanscan-MST, within the scope of the H2020 REMARO project.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average