Machine-learning for enhanced machine reading of non-ideal capture conditions
Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a plurality of filters to the training image to provide a respective plurality of filtered training images, identifying a filter to be associa...
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| Main Author | |
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| Format | Patent |
| Language | English |
| Published |
29.11.2022
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a plurality of filters to the training image to provide a respective plurality of filtered training images, identifying a filter to be associated with the hash pattern based on the plurality of filtered training images, and storing a mapping of the filter to the hash pattern within a set of mapping in a data store. |
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| AbstractList | Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a plurality of filters to the training image to provide a respective plurality of filtered training images, identifying a filter to be associated with the hash pattern based on the plurality of filtered training images, and storing a mapping of the filter to the hash pattern within a set of mapping in a data store. |
| Author | Medina, III, Reynaldo |
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| Notes | Application Number: US201916679833 |
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| Snippet | Implementations of the present disclosure include receiving a training image, providing a hash pattern that is representative of the training image, applying a... |
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| SubjectTerms | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| Title | Machine-learning for enhanced machine reading of non-ideal capture conditions |
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