Digital Image Search Training using Aggregated Digital Images
First Claim
1. In a digital medium image search environment, a method implemented by at least one computing device, the method comprising:
- receiving, by the at least one computing device, a query digital image;
selecting, by the at least one computing device based on the query digital image, at least one positive sample digital image and a plurality of negative sample digital images;
generating, by the at least one computing device, an aggregated digital image by aggregating the at least one positive sample digital image with the plurality of negative sample digital images into a single digital image; and
training, by the at least one computing device, at least one neural network using a loss function as part of machine learning based on a feature comparison between the query digital image and;
the at least one positive sample digital image; and
the plurality of negative sample digital images of the aggregated digital image, respectively.
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Abstract
Digital image search training techniques and machine-learning architectures are described. In one example, a query digital image is received by service provider system, which is then used to select at least one positive sample digital image, e.g., having a same product ID. A plurality of negative sample digital images is also selected by the service provider system based on the query digital image, e.g., having different product IDs. The at least one positive sample digital image and the plurality of negative samples are then aggregated by the service provider system into a single aggregated digital image. At least one neural network is then trained by the service provider system using a loss function based on a feature comparison between the query digital image and samples from the aggregated digital image in a single pass.
4 Citations
20 Claims
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1. In a digital medium image search environment, a method implemented by at least one computing device, the method comprising:
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receiving, by the at least one computing device, a query digital image; selecting, by the at least one computing device based on the query digital image, at least one positive sample digital image and a plurality of negative sample digital images; generating, by the at least one computing device, an aggregated digital image by aggregating the at least one positive sample digital image with the plurality of negative sample digital images into a single digital image; and training, by the at least one computing device, at least one neural network using a loss function as part of machine learning based on a feature comparison between the query digital image and; the at least one positive sample digital image; and the plurality of negative sample digital images of the aggregated digital image, respectively. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. In a digital medium image search training environment, a system comprising:
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a positive sample selection module implemented at least partially in hardware of a computing device to select at least one positive sample digital image from a plurality of digital images based on a query digital image; a negative sample selection module implemented at least partially in hardware of the computing device to select a plurality of negative sample digital images from the plurality of digital images based on the query digital image; an aggregation module implemented at least partially in hardware of the computing device to generate a single aggregated digital image by aggregating the at least one positive sample digital image with the plurality of negative sample digital images; and a training module implemented at least partially in hardware of the computing device to train a neural network using a loss function as part of machine learning to generate a search result from a search of the plurality of digital images, the neural network trained through use of the positive sample digital image and the plurality of negative sample digital images within the single aggregated digital image in a single pass. - View Dependent Claims (13, 14, 15, 16, 17)
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18. Ina digital medium image search training environment, a system comprising:
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means for receiving a search request that includes an input digital image; and means for generating a search result from a plurality of digital images by at least one neural network based on the input digital image of the search request, the at least one neural network trained based on a feature comparison between a query digital image and an aggregated digital image that includes at least one positive sample digital image along with the plurality of negative sample digital images arranged in a grid that are selected based on the query digital image. - View Dependent Claims (19, 20)
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Specification