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
Abstract

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.
Data
File Size Format Processing Access
90569.zip 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. https://doi.org/10.17882/85472