Sulfur-Fumigated Ginger Identification Method Based on Meta-Learning for Different Devices
Tianshu Wang, Jiawang He, Hui Yan, Kongfa Hu, Xichen Yang, Xia Zhang, Jinao Duan, Panagiotis Tsakanikas · 2024
Read Sulfur-Fumigated Ginger Identification Method Based on Meta-Learning for Different Devices by Tianshu Wang, Jiawang He, Hui Yan, Kongfa Hu, Xichen Yang, Xia Zhang, Jinao Duan, Panagiotis Tsakanikas (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11640195.txt.
Description
Tianshu Wang and co-authors spot sulfur-treated ginger in 2024 from phone photos, no lab needed. Sellers fumigate ginger with sulfur to dry it and brighten its color, but the residue harms health. Lab tests are slow and fiddly.
Four phone brands photographed treated and clean ginger. Software trimmed the backgrounds, a deep network pulled features from the shots, and a model learned to sort them, the team reports. A meta-learning twist lets the sorter adapt fast when a new phone or batch arrives, the weak point of photo methods. A phone in a market inspector's pocket could flag suspect ginger on the spot, sending only the doubtful lots to the lab.
Catalog record
| CREATOR | Tianshu Wang, Jiawang He, Hui Yan, Kongfa Hu, Xichen Yang, Xia Zhang, Jinao Duan, Panagiotis Tsakanikas |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |