@inproceedings{60bd3e476e124adfac8cd282b5fbdeaa,
title = "Enhancing Environmental Monitoring Through Multispectral Imaging: The WasteMS Dataset for Semantic Segmentation of Lakeside Waste",
abstract = "Environmental monitoring of lakeside green areas is crucial for environmental protection. Compared to manual inspections, computer vision technologies offer a more efficient solution when deployed on-site. Multispectral imaging provides diverse information about objects under different spectrums, aiding in the differentiation between waste and lakeside lawn environments. This study introduces WasteMS, the first multispectral dataset established for the semantic segmentation of lakeside waste. WasteMS includes a diverse range of waste types in lawn environments, captured under various lighting conditions. We implemented a rigorous annotation process to label waste in images. Representative semantic segmentation frameworks were used to evaluate segmentation accuracy using WasteMS. Challenges encountered when using WasteMS for segmenting waste on lakeside lawns were discussed. The WasteMS dataset is available at https://github.com/zhuqinfeng1999/WasteMS.",
keywords = "Dataset, Lakeside, Multispectral, Semantic segmentation, Waste",
author = "Qinfeng Zhu and Ningxin Weng and Lei Fan and Yuanzhi Cai",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 31st International Conference on Multimedia Modeling, MMM 2025 ; Conference date: 08-01-2025 Through 10-01-2025",
year = "2025",
doi = "10.1007/978-981-96-2054-8_27",
language = "English",
isbn = "9789819620531",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "362--372",
editor = "Ichiro Ide and Ioannis Kompatsiaris and Changsheng Xu and Keiji Yanai and Wei-Ta Chu and Naoko Nitta and Michael Riegler and Toshihiko Yamasaki",
booktitle = "MultiMedia Modeling - 31st International Conference on Multimedia Modeling, MMM 2025, Proceedings",
}