Beijing Baidu Netcom Science Technology Co., Ltd. (20240282024). TRAINING METHOD, METHOD OF DISPLAYING TRANSLATION, ELECTRONIC DEVICE AND STORAGE MEDIUM simplified abstract

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TRAINING METHOD, METHOD OF DISPLAYING TRANSLATION, ELECTRONIC DEVICE AND STORAGE MEDIUM

Organization Name

Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor(s)

Liang Wu of Beijing (CN)

Shanshan Liu of Beijing (CN)

Chengquan Zhang of Beijing (CN)

Kun Yao of Beijing (CN)

TRAINING METHOD, METHOD OF DISPLAYING TRANSLATION, ELECTRONIC DEVICE AND STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240282024 titled 'TRAINING METHOD, METHOD OF DISPLAYING TRANSLATION, ELECTRONIC DEVICE AND STORAGE MEDIUM

The abstract describes a method of training a text erasure model using a generative adversarial network model, as well as a method of displaying a translation, an electronic device, and a storage medium.

  • Simplified Explanation: The patent application outlines a method for training a text erasure model using a generative adversarial network, which involves processing original text block images, training a generator and discriminator, and determining the trained generator as the text erasure model.
  • Key Features and Innovation:

- Training a text erasure model using a generative adversarial network model. - Processing original text block images to obtain simulated text block-erased images. - Alternately training the generator and discriminator with real and simulated text block-erased images. - Determining the trained generator as the text erasure model based on pixel values.

  • Potential Applications:

- Text erasure in images for privacy protection. - Enhancing translation displays by removing text from images. - Electronic devices with improved text erasure capabilities. - Storage mediums for storing text-erased images securely.

  • Problems Solved:

- Ensuring privacy by erasing text from images. - Improving translation display by removing text overlays. - Enhancing electronic devices with advanced text erasure technology.

  • Benefits:

- Enhanced privacy protection. - Improved translation display accuracy. - Advanced text erasure capabilities in electronic devices. - Secure storage of text-erased images.

  • Commercial Applications:

- Title: Advanced Text Erasure Technology for Enhanced Privacy Protection - Potential commercial uses: Security and privacy-focused applications, translation services, electronic devices with text erasure features. - Market implications: Increased demand for privacy-enhancing technologies, improved user experience in translation services, competitive advantage in electronic device market.

  • Questions about Text Erasure Technology:

1. How does the generative adversarial network model improve the training of text erasure models? 2. What are the potential limitations of using text erasure technology in real-world applications?

  • Frequently Updated Research:

- Stay updated on advancements in generative adversarial network models for text erasure applications. - Monitor developments in privacy protection technologies using text erasure methods.


Original Abstract Submitted

a method of training a text erasure model, a method of display a translation, an electronic device, and a storage medium. the training method includes: processing a set of original text block images by using a generator of a generative adversarial network model to obtain a set of simulated text block-erased images; alternately training the generator and a discriminator of the generative adversarial network model by using a set of real text block-erased images and the set of simulated text block-erased images, so as to obtain a trained generator and a trained discriminator; and determining the trained generator as the text erasure model, wherein a pixel value of a text-erased region in a real text block-erased image contained in the set of real text block-erased images is determined based on a pixel value of another region in the real text block-erased image other than the text-erased region.