| Title |
Hyperspectral Classification of Recyclable Plastics in Industrial Setups |
| ID_Doc |
23739 |
| Authors |
Alexakis, G; Maniadakis, M |
| Title |
Hyperspectral Classification of Recyclable Plastics in Industrial Setups |
| Year |
2023 |
| Published |
|
| DOI |
10.1007/978-3-031-34111-3_35 |
| Abstract |
The development of the circular economy has attracted significant research interest in recent years. The present work explores the use of HyperSpectral Imaging (HSI) sensors and Machine Learning (ML) techniques for the categorization of recyclable plastics in challenging industrial conditions. Specifically, we present the pipeline for the pre- and post- processing of the spectral signals and we compare four well-known classifiers in categorizing plastics into seven material types, according to the international standards of the circular economy and material recycling in particular. The obtained results show that hyperspectral technology can contribute to the successful categorization of plastics in industrial conditions. |
| Author Keywords |
Hyperspectral Imaging; Machine Learning; Classifier; Industrial Application; Material Recovery |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001289288100035 |
| WoS Category |
|
| Research Area |
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| PDF |
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