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US Patent 11176443 Application control and text detection from application screen images

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11176443
Date of Patent
November 16, 2021
Patent Application Number
16695030
Date Filed
November 25, 2019
Patent Citations Received
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US Patent 12111646 Robotic process automation with resilient playback of recordings
3
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US Patent 11960930 Automated software robot creation for robotic process automation
4
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US Patent 11968182 Authentication of software robots with gateway proxy for access to cloud-based services
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6
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US Patent 11501549 Document processing using hybrid rule-based artificial intelligence (AI) mechanisms
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US Patent 11630956 Extracting data from documents using multiple deep learning models
9
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US Patent 11663840 Method and system for removing noise in documents for image processing
10
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US Patent 11714831 Data processing and classification
11
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Patent Primary Examiner
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Ali Bayat
Patent abstract

Automation controls and associated text in images displayed by a computer application are automatically detected by way of region-based R-FCN and Faster R-CNN engines. Datasets comprising images containing application controls, where the application controls include images of application where width is greater than height, width is equal to height and height is greater than width are retrieved and each dataset is processed with the R-FCN and Faster R-CNN engines to generate a software robot configured to recognize corresponding application controls. Text is recognized by an optical character recognition system that employs a deep learning system trained to process a plurality of images to identify images representing text within each image and to convert the images representing text to textually encoded data. The deep learning system is trained with training data generated from a corpus of real-life text segments that are generated by a plurality of OCR modules.

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