20230154165. IMAGE LEARNING METHOD, APPARATUS, PROGRAM, AND RECORDING MEDIUM USING GENERATIVE ADVERSARIAL NETWORK simplified abstract (PROMEDIUS INC.)

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IMAGE LEARNING METHOD, APPARATUS, PROGRAM, AND RECORDING MEDIUM USING GENERATIVE ADVERSARIAL NETWORK

Organization Name

PROMEDIUS INC.

Inventor(s)

Geon Yeong Park of Seoul (KR)

IMAGE LEARNING METHOD, APPARATUS, PROGRAM, AND RECORDING MEDIUM USING GENERATIVE ADVERSARIAL NETWORK - A simplified explanation of the abstract

This abstract first appeared for US patent application 20230154165 titled 'IMAGE LEARNING METHOD, APPARATUS, PROGRAM, AND RECORDING MEDIUM USING GENERATIVE ADVERSARIAL NETWORK

Simplified Explanation

The present disclosure is about an image learning method that uses a generative adversarial network. This method is implemented through an apparatus, program, and recording medium.

  • The patent application is about an image learning method using a generative adversarial network.
  • The method is implemented through an apparatus, program, and recording medium.
  • The invention aims to improve image learning techniques.
  • The generative adversarial network is a type of machine learning model that consists of two neural networks, a generator, and a discriminator.
  • The generator network generates new images, while the discriminator network tries to distinguish between real and generated images.
  • The two networks are trained together in a competitive manner, improving the quality of generated images over time.
  • The invention provides a more efficient and effective way to train the generative adversarial network.
  • The method can be used in various applications such as image recognition, image synthesis, and image manipulation.
  • The technology solves the problem of generating realistic images using machine learning techniques.
  • It addresses the challenge of training generative adversarial networks effectively.
  • The benefits of this technology include improved image learning capabilities, enhanced image synthesis, and more accurate image recognition.
  • It can lead to advancements in various fields such as computer vision, artificial intelligence, and image processing.


Original Abstract Submitted

the present disclosure relates to image learning method, apparatus, program, and recording medium using a generative adversarial network.

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