Detecting infection of plant diseases by classifying plant photos
US10761075B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 18, 2019 |
| Grant date | Sep 1, 2020 |
| Priority date | — |
| Expiry date | Oct 18, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/126
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A system and processing methods for configuring and utilizing a convolutional neural network (CNN) for plant disease recognition are disclosed. In some embodiments, the system is programmed to collect photos of infected plants or leaves where regions showing symptoms of infecting diseases are marked. Each photo may have multiple marked regions. Depending on how the symptoms are sized or clustered, one marked region may include only one lesion caused by one disease, while another may include multiple, closely-spaced lesions caused by one disease. The system is programmed to determine anchor boxes having distinct aspect ratios from these marked regions for each convolutional layer of a single shot multibox detector (SSD). For certain types of plants, common diseases lead to relatively many aspect ratios, some having relatively extreme values. The system is programmed to then train the SSD using the marked regions and the anchor boxes and apply the SSD to new photos to identify diseased plants.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.