Fluorescence sensing of nitro explosives based on deep learning
An automated real-time monitoring system is developed for nitro explosives The system precisely identifies multiple nitro explosives with a single AIE probe High data processing efficiency and high target recognition accuracy The deep-learning-based system reduces the labor cost
Authors
- Biao Xiao (ORCID: https://orcid.org/0000-0002-2822-1898)
- J.-Y. Zhang (ORCID: https://orcid.org/0009-0008-3628-3598)
- Xufan Zheng (ORCID: https://orcid.org/0009-0004-1200-5287)
- Xunchang Wang (ORCID: https://orcid.org/0009-0006-6454-0841)
- Yuda Li (ORCID: https://orcid.org/0000-0002-1314-4818)
- Tianyu Hu (ORCID: https://orcid.org/0000-0002-9133-7738)
- Renqiang Yang (ORCID: https://orcid.org/0000-0001-6794-7416)
- Jingyi Xiong
- Huimin Xiang (ORCID: https://orcid.org/0000-0003-2617-911X)
Institutions
- Jianghan University (CN)
- Wuhan Institute of Technology (CN)
Publication Details
- Journal
- Cell Reports Physical Science
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1016/j.xcrp.2025.102690
- Primary Topic
- Spectroscopy Techniques in Biomedical and Chemical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Jianghan University