The BeachLitter Dataset v2022

Date 2022-01-06
Temporal extent 2011 -2019
Author(s) Sugiyama Daisuke1, Hidaka Mitsuko1, Matsuoka Daisuke1, Murakami Koshiro1, Kako Shin’ichiro2
Affiliation(s) 1 : JAMSTEC, Research Institute for Value-Added-Information Generation, Kanagawa, Japan
2 : Kagoshima University, Graduate School of Science and Engineering, Department of Engineering, Ocean Civil Engineering Program, Kagoshima, Japan
DOI 10.17882/85472
Publisher SEANOE
Keyword(s) Beach litter, Marine plastics, Beach monitoring, Deep learning, Image segmentation, AI

8-class segmentation masks by high-quality manual pixel-by-pixel annotations, corresponding 3500 beach litter images from 2011 to 2019 in Yamagata Prefecture, Japan. (papers are under review)

Licence CC-BY-NC-SA
Acknowledgements We are grateful to the Shonai General Branch Office in Yamagata Prefecture for providing the beach litter images. We received valuable support from the Non-Profit Organization Partnership Office for communicating with the Yamagata Prefecture government office.
File Size Format Processing Access 937 MB IMAGE Open access
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How to cite 

Sugiyama Daisuke, Hidaka Mitsuko, Matsuoka Daisuke, Murakami Koshiro, Kako Shin’ichiro (2022). The BeachLitter Dataset v2022. SEANOE.

In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :

Sugiyama Daisuke, Hidaka Mitsuko, Matsuoka Daisuke, Murakami Koshiro, Kako Shin'ichiro (2022). The BeachLitter dataset for image segmentation of beach litter. Data in Brief, 42, 108072-.