Generating and utilizing normalized scores for classifying digital objects
First Claim
Patent Images
1. A method comprising:
- identifying a set of one or more digital training images tagged with information identifying a known object, the known object portrayed in each image in the set of one or more tagged digital training images;
generating, by at least one processor and utilizing the information identifying the known object, a classification score with regard to an unknown object portrayed in a probe digital image, the classification score indicating a likelihood that the unknown object portrayed in the probe digital image corresponds to the known object portrayed in the set of one or more tagged digital training images;
transforming the classification score into a normalized classification score based on the number of tagged digital training images in the set of one or more tagged digital training images; and
determining whether the unknown object portrayed in the probe digital image corresponds to the known object portrayed in the set of one or more tagged digital training images by comparing the normalized classification score with a second normalized classification score corresponding to a second known object portrayed in a second set of one or more tagged digital training images and generated based on the number of tagged digital training images in the second set of one or more tagged digital training images.
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Abstract
The present disclosure is directed toward systems and methods that enable more accurate digital object classification. In particular, disclosed systems and methods address inaccuracies in digital object classification introduced by variations in classification scores. Specifically, in one or more embodiments, disclosed systems and methods generate probability functions utilizing digital test objects and transform classifications scores into normalized classification scores utilizing probability functions. Disclosed systems and methods utilize normalized classification scores to more accurately classify and identify digital objects in a variety of applications.
19 Citations
20 Claims
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1. A method comprising:
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identifying a set of one or more digital training images tagged with information identifying a known object, the known object portrayed in each image in the set of one or more tagged digital training images; generating, by at least one processor and utilizing the information identifying the known object, a classification score with regard to an unknown object portrayed in a probe digital image, the classification score indicating a likelihood that the unknown object portrayed in the probe digital image corresponds to the known object portrayed in the set of one or more tagged digital training images; transforming the classification score into a normalized classification score based on the number of tagged digital training images in the set of one or more tagged digital training images; and determining whether the unknown object portrayed in the probe digital image corresponds to the known object portrayed in the set of one or more tagged digital training images by comparing the normalized classification score with a second normalized classification score corresponding to a second known object portrayed in a second set of one or more tagged digital training images and generated based on the number of tagged digital training images in the second set of one or more tagged digital training images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system comprising:
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at least one processor; and at least one non-transitory computer readable storage medium storing instructions that, when executed by the at least one processor, cause the system to; identify a set of one or more digital training images tagged with information identifying a known object, the known object portrayed in each image in the set of one or more tagged digital training images; generate, utilizing the information identifying the known object, a classification score with regard to an unknown object portrayed in a probe digital image, the classification score indicating a likelihood that the unknown object portrayed in the probe digital image corresponds to the known object portrayed in the set of one or more tagged digital training images; transform the classification score into a normalized classification score based on the number of tagged digital training images in the set of one or more tagged digital training images; and determine whether the unknown object portrayed in the probe digital image corresponds to the known object portrayed in the set of one or more tagged digital training images by comparing the normalized classification score with a second normalized classification score corresponding to a second known object portrayed in a second set of one or more tagged digital training images and generated based on the number of tagged digital training images in the second set of one or more tagged digital training images. - View Dependent Claims (11, 12, 13, 14, 15)
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16. A method comprising:
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identifying a set of one or more digital training objects tagged with information identifying a known classification, the known classification corresponding to each of the digital training objects in the set of one or more tagged digital training objects; generating, by at least one processor and utilizing the information identifying the known classification, a classification score with regard to an unknown digital object, the classification score indicating a likelihood that the unknown digital object corresponds to the known classification; transforming the classification score into a normalized classification score based on the number of tagged digital training objects; and determining whether the unknown digital object corresponds to the known classification by comparing the normalized classification score with a second normalized classification score corresponding to a second known classification of a second set of one or more digital training objects and generated based on the number of tagged digital training objects in the second set of one or more tagged digital training objects. - View Dependent Claims (17, 18, 19, 20)
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Specification