Machine Learning Advancements and Strategies in Microplastic and Nanoplastic Detection
Fudan University · Shanghai Institute of Pollution Control and Ecological Security
Abstract
Microplastics (MPs) and nanoplastics (NPs) present formidable global environmental challenges with serious risks to human health and ecosystem sustainability. Despite their significance, the accurate assessment of environmental MP and NP pollution remains hindered by limitations in existing detection technologies, such as low resolution, substantial data volumes, and prolonged imaging times. Machine learning (ML) provides a promising pathway to overcome these challenges by enabling efficient data processing and complex pattern recognition. This systematic Review aims to address these gaps by examining the role of ML techniques combined with spectroscopy in improving the detection and characterization of NPs.…
Citation impact
- FWCI
- 24.25
- Percentile
- 100%
- References
- 113
Authors
5- LXLifang Xie
Fudan University, Shanghai Institute of Pollution Control and Ecological Security
- MMMinglu Ma
Fudan University, Shanghai Institute of Pollution Control and Ecological Security
- QGQiuyue Ge
Fudan University, Shanghai Institute of Pollution Control and Ecological Security
- YLYangyang Liu
Fudan University, Shanghai Institute of Pollution Control and Ecological Security
- LZLiwu ZhangCorresponding
Fudan University, Shanghai Institute of Pollution Control and Ecological Security
Topics & keywords
- Artificial intelligence
- Computer science
- Environmental science
- Risk analysis (engineering)
- Business