Method and system for detecting Fusarium moniliforme species of rice seed
US12385825B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 22, 2023 |
| Grant date | Aug 12, 2025 |
| Priority date | — |
| Expiry date | Apr 10, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30128
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method and system for detecting Fusarium moniliforme species of rice seeds are provided, relating to the field of rapid quality detection of rice seeds. The method includes: inputting a hyperspectral image of to-be-tested rice seeds to a model for detecting Fusarium moniliforme species of rice seed, to determine a test result of the rice seeds, where the test result is no Fusarium moniliforme or a Fusarium species. The model for detecting Fusarium moniliforme species of rice seed is determined based on activated wavelengths and an original deep convolutional neural network; the activated wavelengths are wavelengths activated by a trained deep convolutional neural network upon correct classification; and the trained deep convolutional neural network is a neural network obtained by training the original deep convolutional neural network based on the training set.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.