US 12,080,054 B2
Systems and methods for detecting small objects in an image using a neural network
Sergey Ulasen, Moscow (RU); Vasyl Shandyba, Dnipro (UA); Alexander Snorkin, Moscow (RU); Artem Shapiro, Dnipro (UA); Andrey Adaschik, Moscow (RU); Serguei Beloussov, Costa del Sol (SG); and Stanislav Protasov, Moscow (RU)
Assigned to Acronis International GmbH, Schaffhausen (CH)
Filed by Acronis International GmbH, Schaffhausen (CH)
Filed on Mar. 8, 2022, as Appl. No. 17/689,403.
Claims priority of provisional application 63/159,204, filed on Mar. 10, 2021.
Prior Publication US 2022/0292817 A1, Sep. 15, 2022
Int. Cl. G06V 10/82 (2022.01); G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 20/40 (2022.01)
CPC G06V 10/82 (2022.01) [G06N 3/045 (2023.01); G06V 10/764 (2022.01); G06V 20/42 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method for detecting small objects in an image using a neural network, the method comprising:
receiving a first neural network that is trained on a dataset comprising a plurality of images depicting various objects;
identifying a first structure of the first neural network, the first structure indicative of each layer and layer size in the first neural network;
determining, based on the first structure, whether the first neural network can classify an object less than a threshold size in an input image;
in response to determining that the first neural network cannot classify the object, identifying a subset of detection layers in the first neural network;
generating a second neural network that has a second structure in which the subset of detection layers are replaced by at least one layer not in the subset;
training the second neural network with the dataset; and
receiving, from the second neural network, a classification of the object less than the threshold size in the input image.