US 11,989,871 B2
Model training apparatus and method
Joseph Henry, Edinburgh (GB); and Aneta Lisowska, Edinburgh (GB)
Assigned to CANON MEDICAL SYSTEMS CORPORATION, Otawara (JP)
Filed by CANON MEDICAL SYSTEMS CORPORATION, Otawara (JP)
Filed on Jun. 2, 2021, as Appl. No. 17/336,968.
Prior Publication US 2022/0392048 A1, Dec. 8, 2022
Int. Cl. G06T 7/00 (2017.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06T 7/11 (2017.01)
CPC G06T 7/0004 (2013.01) [G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06T 7/11 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30016 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus comprising processing circuitry configured to:
receive a first model and a second model, wherein:
the first model is trained to perform a first task;
the first model is trained on first training data of a first domain;
the second model is trained on second, different training data; and at least one of a) and b):—
a) the second model is trained to perform a second task that is different from the first task;
b) the second training data is data of a second domain that is different from the first domain;
determine difference information that is representative of a difference between the first model and the second model and/or between the first task and the second task and/or between the first domain and the second domain; and
generate a third model using the first model, the second model and the difference information, wherein the generating of the third model comprises training the third model to perform both of the first task and the second task and/or to operate on both the first domain and the second domain.