Google llc (20240238967). Domain Adaptation Using Simulation to Simulation Transfer simplified abstract
Domain Adaptation Using Simulation to Simulation Transfer
Organization Name
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 20240238967 titled 'Domain Adaptation Using Simulation to Simulation Transfer
Simplified Explanation
The patent application describes methods, systems, and apparatus for training a generator neural network to adapt input images.
- The technology involves computer programs encoded on computer storage media.
- It focuses on training a generator neural network to adapt input images.
Key Features and Innovation
- Utilizes computer programs encoded on computer storage media.
- Trains a generator neural network to adapt input images.
Potential Applications
The technology can be applied in various fields such as image processing, computer vision, and artificial intelligence.
Problems Solved
Addresses the need for efficient adaptation of input images by a generator neural network.
Benefits
- Improved image processing capabilities.
- Enhanced performance of generator neural networks.
Commercial Applications
Title: "Enhancing Image Processing with Generator Neural Networks" This technology can be used in industries such as healthcare, security, and entertainment for image enhancement and analysis.
Questions about the Technology
1. How does the technology improve the performance of generator neural networks? 2. What are the potential applications of this technology in the field of artificial intelligence?
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.
