Neural network based scene text recognition [US Patent US 2022/0237403 A1]
A system uses a neural network based model to perform scene text recognition. The system achieves high accuracy of prediction of text from scenes based on a neural network architecture that uses double attention mechanism. The neural network based model includes a convolutional neural network compon...
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sg-smu-ink.sis_research-108082024-12-18T02:58:25Z Neural network based scene text recognition [US Patent US 2022/0237403 A1] ZHOU, Pan TANG, Peng XU, Ran HOI, Steven Chu Hong A system uses a neural network based model to perform scene text recognition. The system achieves high accuracy of prediction of text from scenes based on a neural network architecture that uses double attention mechanism. The neural network based model includes a convolutional neural network component that outputs a set of visual features and an attention extractor neural network component that determines attention scores based on the visual features. The visual features and the attention scores are combined to generate mixed features that are provided as input to a character recognizer component that determines a second attention score and recognizes the characters based on the second attention score. The system trains the neural network based model by adjusting the neural network parameters to minimize a multi-class gradient harmonizing mechanism (GHM) loss. The multi-class GHM loss varies based on a level of difficulty of the sample. 2022-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/9808 https://ink.library.smu.edu.sg/context/sis_research/article/10808/viewcontent/2024_US_Patent_OCR.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering Systems Architecture |
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Software Engineering Systems Architecture ZHOU, Pan TANG, Peng XU, Ran HOI, Steven Chu Hong Neural network based scene text recognition [US Patent US 2022/0237403 A1] |
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A system uses a neural network based model to perform scene text recognition. The system achieves high accuracy of prediction of text from scenes based on a neural network architecture that uses double attention mechanism. The neural network based model includes a convolutional neural network component that outputs a set of visual features and an attention extractor neural network component that determines attention scores based on the visual features. The visual features and the attention scores are combined to generate mixed features that are provided as input to a character recognizer component that determines a second attention score and recognizes the characters based on the second attention score. The system trains the neural network based model by adjusting the neural network parameters to minimize a multi-class gradient harmonizing mechanism (GHM) loss. The multi-class GHM loss varies based on a level of difficulty of the sample. |
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text |
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ZHOU, Pan TANG, Peng XU, Ran HOI, Steven Chu Hong |
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ZHOU, Pan TANG, Peng XU, Ran HOI, Steven Chu Hong |
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ZHOU, Pan |
title |
Neural network based scene text recognition [US Patent US 2022/0237403 A1] |
title_short |
Neural network based scene text recognition [US Patent US 2022/0237403 A1] |
title_full |
Neural network based scene text recognition [US Patent US 2022/0237403 A1] |
title_fullStr |
Neural network based scene text recognition [US Patent US 2022/0237403 A1] |
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Neural network based scene text recognition [US Patent US 2022/0237403 A1] |
title_sort |
neural network based scene text recognition [us patent us 2022/0237403 a1] |
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Institutional Knowledge at Singapore Management University |
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2022 |
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https://ink.library.smu.edu.sg/sis_research/9808 https://ink.library.smu.edu.sg/context/sis_research/article/10808/viewcontent/2024_US_Patent_OCR.pdf |
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