VISUAL OBJECT RECOGNITION
First Claim
1. A computer-implemented method for training an object-recognition neural network to identify an object in a computer-readable image, the method comprising:
- assigning, using a processor system, a first neural network for determining a visual alignment model of the images, wherein the visual alignment model is used to determine a normalized alignment of an object in input images;
assigning, using the processor system, a second neural network for determining a visual representation model of the images, wherein the visual representation model is used to recognize the object in the input images;
determining the visual alignment model by training the first neural network;
determining the visual representation model by training the second neural network;
determining a combined object recognition model by training a combination of the first neural network and the second neural network; and
recognizing the object in the computer-readable image based on the combined object recognition model by passing the computer-readable image through each of the combined neural networks.
1 Assignment
0 Petitions
Accused Products
Abstract
Technical solutions are described for training an object-recognition neural network that identifies an object in a computer-readable image. An example method includes assigning a first neural network for determining a visual alignment model of the images for determining a normalized alignment of the object. The method further includes assigning a second neural network for determining a visual representation model of the images for recognizing the object. The method further includes determining the visual alignment model by training the first neural network and determining the visual representation model by training the second neural network independent of the first. The method further includes determining a combined object recognition model by training a combination of the first neural network and the second neural network. The method further includes recognizing the object in the image based on the combined object recognition model by passing the image through each of the neural networks.
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Citations
20 Claims
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1. A computer-implemented method for training an object-recognition neural network to identify an object in a computer-readable image, the method comprising:
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assigning, using a processor system, a first neural network for determining a visual alignment model of the images, wherein the visual alignment model is used to determine a normalized alignment of an object in input images; assigning, using the processor system, a second neural network for determining a visual representation model of the images, wherein the visual representation model is used to recognize the object in the input images; determining the visual alignment model by training the first neural network; determining the visual representation model by training the second neural network; determining a combined object recognition model by training a combination of the first neural network and the second neural network; and recognizing the object in the computer-readable image based on the combined object recognition model by passing the computer-readable image through each of the combined neural networks. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system for training an object-recognition neural network to identify an object in a computer-readable image, the system comprising:
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a memory; and a processor communicatively coupled to the memory, wherein the processor is configured to; assign a first neural network for determining a visual alignment model of the images, wherein the visual alignment model is used to determine a normalized alignment of an object in input images; assign a second neural network for determining a visual representation model of the images, wherein the visual representation model is used to recognize the object in the input images; determine the visual alignment model by training the first neural network; determine the visual representation model by training the second neural network; determine a combined object recognition model by training a combination of the first neural network and the second neural network; and recognize the object in the computer-readable image based on the combined object recognition model by passing the computer-readable image through each of the combined neural networks. - View Dependent Claims (12, 13, 14, 15, 16)
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17. A computer program product for training an object-recognition neural network to identify an object in a computer-readable image, the computer program product comprising a non-transitory computer readable storage medium, the computer readable storage medium comprising computer executable instructions, wherein the computer readable storage medium comprises instructions to:
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assign a first neural network for determining a visual alignment model of the images, wherein the visual alignment model is used to determine a normalized alignment of an object in input images; assign a second neural network for determining a visual representation model of the images, wherein the visual representation model is used to recognize the object in the input images; determine the visual alignment model by training the first neural network; determine the visual representation model by training the second neural network; determine a combined object recognition model by training a combination of the first neural network and the second neural network; and recognize the object in the computer-readable image based on the combined object recognition model by passing the computer-readable image through each of the combined neural networks. - View Dependent Claims (18, 19, 20)
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Specification