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AssigneeMicrosoft Technology Licensing, LLC
InventorsOren BARKAN, Noam RAZIN, Noam KOENIGSTEIN, Roy HIRSCH, Nir NICE
Estimating the term…
Machine learning multiple features of an item depicted in images. Upon accessing multiple images that depict the item, a neural network is used to machine train on the plurality of images to generate embedding vectors for each of multiple features of the item. For each of multiple features of the item depicted in the images, in each iteration of the machine learning, the embedding vector is converted into a probability vector that represents probabilities that the feature has respective values. That probability vector is then compared with a value vector representing the actual value of that feature in the depicted item, and an error between the two vectors is determined. That error is used to adjust parameters of the neural network used to generate the embedding vector, allowing for the next iteration in the generation of the embedding vectors. These iterative changes continue thereby training the neural network.
A computer system that trains a neural network to identify features of an item embodied in an image and to use the neural network to identify other items that have similar features to said features, the computer system comprising:
A method for training a neural network to identify features of an item embodied in an image and for using the neural network to identify other items that have similar features to said features, the method comprising:
One or more hardware storage devices that store instructions that are executable by one or more processors to cause the one or more processors to:
Dependencies are inferred from the claim text.