Weakly supervised anomaly detection and segmentation in images
US10672115B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 6, 2017 |
| Grant date | Jun 2, 2020 |
| Priority date | — |
| Expiry date | Dec 6, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed for processing an image to detect anomalous pixels. An image classification is received from a trained convolutional neural network (CNN) for an input image with a positive classification being defined to represent detection of an anomaly in the image and a negative classification being defined to represent absence of an anomaly. A backward propagation analysis of the input image for each layer of the CNN generates an attention mapping that includes a positive attention map and a negative attention map. A positive mask is generated based on intensity thresholds of the positive attention map and a negative mask is generated based on intensity thresholds of the negative attention map. An image of segmented anomalous pixels is generated based on an aggregation of the positive mask and the negative mask.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.