US 12,423,967 B2
Method of augmenting the number of labeled images for training a neural network
Astrid Berg, Mortsel (BE); Eva Vandersmissen, Mortsel (BE); and Katja Buehler, Mortsel (BE)
Assigned to Agfa NV, Mortsel (BE); and VRVIS Zentrum füVirtual Reality und Visualisierung Forschungs—GmbH, Vienna (AT)
Appl. No. 18/247,559
Filed by AGFA NV, Mortsel (BE); and VRVIS Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna (AT)
PCT Filed Oct. 1, 2021, PCT No. PCT/EP2021/077050
§ 371(c)(1), (2) Date Mar. 31, 2023,
PCT Pub. No. WO2022/073856, PCT Pub. Date Apr. 14, 2022.
Claims priority of application No. 20200295 (EP), filed on Oct. 6, 2020.
Prior Publication US 2023/0377323 A1, Nov. 23, 2023
Int. Cl. G06V 10/82 (2022.01); G06V 10/74 (2022.01); G06V 10/75 (2022.01); G06V 10/774 (2022.01)
CPC G06V 10/82 (2022.01) [G06V 10/758 (2022.01); G06V 10/761 (2022.01); G06V 10/7753 (2022.01)] 4 Claims
 
1. A method of augmenting the number of labeled images for training a neural network, the method comprising:
starting from a dataset of labeled images with corresponding segmentation masks and a dataset of unlabeled images,
gathering for a given image i in a data set of labeled images a number of images with metadata that have at least one item with the same value in said dataset of unlabeled images so as to form a data sub-set Sim i,
training a multiclass segmentation neural network on said labeled images thereby generating segmentation masks for the images in sub-set Sim i,
on the basis of these segmentation masks judging similarity between images of Sim i and image i and finding most similar image(s) in Sim i by computing histograms of segmentation masks of image i and images in Sim i and by comparing them, and
transferring the histogram of the most similar images in Sim i to given image i.