Model training using partially-annotated images

Model training using partially-annotated images

Methods and systems for training a model labeling two or more organic structures in an image. One method includes receiving a set of training images including a first plurality of images and a second plurality of images. Each of the first plurality of images including a label for a first subset of t...

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Hauptverfasser: Wang, Hongzhi, Francis, John Paul, Syeda-Mahmood, Tanveer Fathima
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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creator Wang, Hongzhi
Francis, John Paul
Syeda-Mahmood, Tanveer Fathima
description Methods and systems for training a model labeling two or more organic structures in an image. One method includes receiving a set of training images including a first plurality of images and a second plurality of images. Each of the first plurality of images including a label for a first subset of the two or more organic structures and each of the second plurality of images including a label for a second subset of the two or more organic structures, the second subset being different than the first subset. The method also includes training the model using the first plurality of images, the second plurality of images, and a label merging function mapping a label included in the first plurality of images to a label included in the second plurality of images.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
HANDLING RECORD CARRIERS
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
title Model training using partially-annotated images
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