CPC G06V 10/454 (2022.01) [G06F 18/214 (2023.01); G06F 18/2193 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 5/002 (2013.01); G06T 5/50 (2013.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06T 2207/20084 (2013.01)] | 19 Claims |
1. An apparatus configured to train an image processing model for removing noise from an image containing the noise, the apparatus comprising:
at least one processor;
a memory coupled to the at least one processor storing instructions that, when executed by the at least one processor, cause the at least one processor to function as:
an acquisition unit configured to acquire a low-noise image and a plurality of high-noise images having more noise than the low-noise image, the low-noise image being training data for training the image processing model comprising one neural network, the plurality of high-noise images corresponding to a scene in the low-noise image and each having different noise patterns;
an error calculation unit configured to calculate each of errors between a plurality of output images and the low-noise image, each of the plurality of output images being acquired by inputting a different one of the plurality of high-noise images to the one neural network;
a stability calculation unit configured to calculate a stability against the noise based on an error between the plurality of output images; and
a training unit configured to train the one neutral network using a loss function based on the calculated errors and the calculated stability.
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