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Samsung electronics co., ltd. (20240267592). DISPLAY DEVICE AND OPERATION METHOD THEREOF simplified abstract

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DISPLAY DEVICE AND OPERATION METHOD THEREOF

Organization Name

samsung electronics co., ltd.

Inventor(s)

Jongin Lee of Suwon-si (KR)

Sehyun Kim of Suwon-si (KR)

Kwansik Yang of Suwon-si (KR)

Kilsoo Choi of Suwon-si (KR)

DISPLAY DEVICE AND OPERATION METHOD THEREOF - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240267592 titled 'DISPLAY DEVICE AND OPERATION METHOD THEREOF

Simplified Explanation: The patent application describes a display device and its operation method, which involves analyzing displayed images using neural network models to control the execution environment of content.

  • The display device includes a display, input/output interface, communication interface, memory, and processor.
  • It displays images received from an electronic device and analyzes them using neural network models.
  • The device determines when content execution starts, obtains attribute information of the content, and controls the execution environment based on this information.

Key Features and Innovation:

  • Utilizes neural network models to analyze displayed images and control content execution.
  • Enhances user experience by automatically adjusting the execution environment based on content attributes.
  • Integrates multiple components such as display, interfaces, memory, and processor for efficient operation.

Potential Applications:

  • Smart TVs and monitors with advanced content analysis capabilities.
  • Interactive displays in public spaces for customized content delivery.
  • Gaming consoles with adaptive gameplay settings based on content attributes.

Problems Solved:

  • Streamlines the process of analyzing and controlling content execution on display devices.
  • Improves user interaction by automatically adjusting settings based on content attributes.
  • Enhances overall viewing experience by optimizing the execution environment.

Benefits:

  • Enhanced user experience with personalized content settings.
  • Efficient content analysis and execution control.
  • Seamless integration of neural network models for intelligent operations.

Commercial Applications: "Intelligent Display Device for Enhanced Content Control and Analysis" This technology can revolutionize the display industry by offering smart devices that adapt to content attributes, providing a more immersive and tailored viewing experience. Potential commercial applications include smart TVs, interactive displays, and gaming consoles that offer advanced content analysis and execution control features.

Questions about Display Device Technology: 1. How does the use of neural network models improve content control on display devices? 2. What are the potential implications of this technology for the future of display devices?

Frequently Updated Research: Ongoing research in neural network models and image analysis techniques can further enhance the capabilities of display devices in analyzing and controlling content execution. Stay updated on advancements in artificial intelligence and display technology to explore new possibilities for intelligent content management.


Original Abstract Submitted

according to various embodiments, a display device and an operation method thereof are disclosed. the disclosed display device includes: a display, an input/output interface comprising circuitry, a communication interface comprising communication circuitry, a memory in which one or more instructions are stored, and at least one processor, comprising processing circuitry, individually and/or collectively, configured to execute the one or more instructions stored in the memory to cause the display device to: display an image screen received from an electronic device connected to the display device, determine whether execution of content starts by analyzing the displayed image screen using a first neural network model, call a second neural network model based on determining that the execution of the content starts, obtain attribute information of the content by analyzing the image screen of the content using the second neural network model, and control an execution environment of the content based on the obtained attribute information.

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