Invention Application
- Patent Title: NEURAL NETWORK BASED SCENE TEXT RECOGNITION
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Application No.: US17161378Application Date: 2021-01-28
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Publication No.: US20220237403A1Publication Date: 2022-07-28
- Inventor: Pan Zhou , Peng Tang , Ran Xu , Chu Hong Hoi
- Applicant: salesforce.com, inc.
- Applicant Address: US CA San Francisco
- Assignee: salesforce.com, inc.
- Current Assignee: salesforce.com, inc.
- Current Assignee Address: US CA San Francisco
- Main IPC: G06K9/32
- IPC: G06K9/32 ; G06K9/62 ; G06N3/08 ; G06N3/04

Abstract:
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.
Public/Granted literature
- US11915500B2 Neural network based scene text recognition Public/Granted day:2024-02-27
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