Computer vision for solid waste sorting : A critical review of academic research
Copyright © 2022 Elsevier Ltd. All rights reserved.
| Veröffentlicht in: | Waste management (New York, N.Y.). - 1999. - 142(2022) vom: 01. Apr., Seite 29-43 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | Waste management (New York, N.Y.) |
| Schlagworte: | Journal Article Review Computer vision Deep learning Image recognition Machine learning Municipal solid waste Waste sorting Industrial Waste Solid Waste |
| Zusammenfassung: | Copyright © 2022 Elsevier Ltd. All rights reserved. Waste sorting is highly recommended for municipal solid waste (MSW) management. Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW sorting. Particularly, the field of CV-enabled waste sorting is experiencing an unprecedented explosion of academic research. However, little attention has been paid to understanding its evolvement path, status quo, and prospects and challenges ahead. To address the knowledge gap, this paper provides a critical review of academic research that focuses on CV-enabled MSW sorting. Prevalent CV algorithms, in particular their technical rationales and prediction performance, are introduced and compared. The distribution of academic research outputs is also examined from the aspects of waste sources, task objectives, application domains, and dataset accessibility. The review discovers a trend of shifting from traditional machine learning to deep learning algorithms. The robustness of CV for waste sorting is increasingly enhanced owing to the improved computation powers and algorithms. Academic studies were unevenly distributed in different sectors such as household, commerce and institution, and construction. Too often, researchers reported some preliminary studies using simplified environments and artificially collected data. Future research efforts are encouraged to consider the complexities of real-world scenarios and implement CV in industrial waste sorting practice. This paper also calls for open sharing of waste image datasets for interested researchers to train and evaluate their CV algorithms |
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| Beschreibung: | Date Completed 14.03.2022 Date Revised 14.03.2022 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1879-2456 |
| DOI: | 10.1016/j.wasman.2022.02.009 |