18605452. Domain Adaptation Using Simulation to Simulation Transfer simplified abstract (GOOGLE LLC)

Domain Adaptation Using Simulation to Simulation Transfer

Organization Name

GOOGLE LLC

Inventor(s)

Paul Wohlhart of Sunnyvale CA (US)

Stephen James of Santa Clara CA (US)

Mrinal Kalakrishnan of Palo Alto CA (US)

Konstantinos Bousmalis of London (GB)

Domain Adaptation Using Simulation to Simulation Transfer - A simplified explanation of the abstract

This abstract first appeared for US patent application 18605452 titled 'Domain Adaptation Using Simulation to Simulation Transfer

Simplified Explanation: This patent application describes methods, systems, and apparatus for training a generator neural network to adapt input images.

Key Features and Innovation:

• Training a generator neural network to adapt input images
• Computer programs encoded on computer storage media
• Enhancing the adaptability of input images through neural network training

Potential Applications: This technology could be applied in various fields such as image processing, computer vision, and artificial intelligence.

Problems Solved: This technology addresses the need for improving the adaptability of input images in neural networks.

Benefits:

• Enhanced adaptability of input images
• Improved performance of neural networks in image processing tasks

Commercial Applications: Potential commercial uses include image editing software, automated image enhancement tools, and AI-powered image recognition systems.

Questions about Training a Generator Neural Network to Adapt Input Images: 1. How does training a generator neural network improve the adaptability of input images? 2. What are the potential applications of this technology in image processing and computer vision?

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Original Abstract Submitted

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a generator neural network to adapt input images.