Machine learning model and neural network to predict object characteristics from digital image similarities

A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a computer including a processor, cause the computer to perform functions configured by the computer-executable instructions, wherein the instructions comprise:

• input, to a machine learning model, a target product image in digital form that represents a target product;
• identify, by the machine learning model, a set of similar product images by comparing digital pixel data of the target product image to digital pixel data of known product images and generating a similarity score between the target product image and each of similar product images;
• for each similar product image of the set of similar product images, retrieve product attributes including historical event data associated with each similar product image;
• and
• generate a predicted characteristic for the target product represented in the target product image based at least on the historical event data for a given similar product combined with the similarity score of the given similar product.

A computing system, comprising:

• at least one processor connected to at least one memory;
• a non-transitory computer readable medium including instructions stored thereon that, when executed by the at least one processor, cause the at least one processor to:
• input, to a machine learning model, a target product image in digital form that represents a target product;
• compare, by the machine learning model, at least digital pixel data of the target product image to digital pixel data from a group of known product images;
• generate, by the machine learning model, a similarity score between the product image and one or more known product images from the group of known product images based at least on the digital pixel data;
• identify, by the machine learning model, a set of similar product images based at least in part on the similarity score of the one or more known product images;
• for each similar product image of the set of similar product images, retrieve product attributes including historical event data associated with each similar product image;
• and
• generate a predicted characteristic model including a predicted characteristic for the target product represented in the target product image based at least on the historical event data for a given similar product combined with the similarity score of the given similar product.