Neural network image analysis
Номер патента: EP3921796A1
Опубликовано: 15-12-2021
Автор(ы): Delaram Behnami, Purang Abolmaesumi, Teresa Tsang, Zhibin Liao
Принадлежит: University of British Columbia
Опубликовано: 15-12-2021
Автор(ы): Delaram Behnami, Purang Abolmaesumi, Teresa Tsang, Zhibin Liao
Принадлежит: University of British Columbia
Реферат: A computer-implemented method of facilitating neural network image analysis involves receiving signals representing a set of images, causing at least one neural network function to be applied to the set of images to determine at least one property confidence distribution parameter, and causing a cumulative distribution function defined at least in part by the at least one property confidence distribution parameter to be applied to a plurality of ranges, each range associated with a respective property that may be associated with the set of images, to determine a plurality of property confidences, each of the property confidences representing a confidence that the set of images should be associated with a respective one of the properties. Other methods, systems, and computer-readable media are disclosed.
Constrained training of artificial neural networks using labelled medical data of mixed quality
Номер патента: EP4058944A1. Автор: Daniel Bystrov,Stewart Young,Bernd Lundt,Jens Von Berg,Nataly Wieberneit,Sven KROENKE. Владелец: Koninklijke Philips NV. Дата публикации: 2022-09-21.