US 11,809,985 B2
Algorithmic apparel recommendation
Luisa F. Polanía Cabrera, Sunnyvale, CA (US); and Satyajit Vishram Gupte, Sunnyvale, CA (US)
Assigned to Target Brands, Inc., Minneapolis, MN (US)
Filed by Target Brands, Inc., Minneapolis, MN (US)
Filed on Jan. 31, 2020, as Appl. No. 16/778,522.
Claims priority of provisional application 62/802,533, filed on Feb. 7, 2019.
Prior Publication US 2020/0257976 A1, Aug. 13, 2020
Int. Cl. G06Q 30/00 (2023.01); G06N 3/08 (2023.01); G06Q 30/0601 (2023.01)
CPC G06N 3/08 (2013.01) [G06Q 30/0631 (2013.01); G06Q 30/0643 (2013.01)] 15 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
obtaining a pair of images of apparel items;
providing the pair of images as input to a trained neural network, wherein the trained neural network includes a first subnetwork comprising a left branch and a right branch;
processing the pair of images with the trained neural network, wherein processing the pair of images includes:
generating first feature embeddings for a first image of the pair of images using the left branch of the first subnetwork and generating second feature embeddings for a second image of the pair of images using the right branch of the first subnetwork;
using a combiner, generating a combined feature vector of the first feature embeddings and the second feature embeddings by calculating a Hadamard product of the first feature embeddings and the second feature embeddings; and
mapping the combined feature vector to a compatibility score using a readout function of a second subnetwork, the second subnetwork including a fully connected (FC) neural network;
obtaining the compatibility score as output from the second subnetwork of the trained neural network; and
upon determining that the compatibility score is over a predetermined threshold value, recommending that a first apparel item associated with the first image and a second apparel item associated with second image are compatible.