Nvidia corporation (20240095880). USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE simplified abstract
Contents
- 1 USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE
Organization Name
Inventor(s)
Shiqiu Liu of Cupertino CA (US)
Jussi Rasanen of Helsinki (FI)
Michael Ranzinger of Park City UT (US)
Guilin Liu of San Jose CA (US)
Andrew Tao of Los Altos CA (US)
Bryan Christopher Catanzaro of Los Altos Hills CA (US)
USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095880 titled 'USING A NEURAL NETWORK TO GENERATE AN UPSAMPLED IMAGE
Simplified Explanation
The patent application describes using neural networks to generate an upsampled version of images based on denoised versions of the same images. It also involves generating high-resolution images from noisy low-resolution images and separating components of low-resolution images before denoising.
- Neural networks used to generate upsampled images based on denoised versions of the same images
- Upsampling high-resolution images from noisy low-resolution images
- Separating components of low-resolution images before denoising
Potential Applications
This technology could be applied in:
- Image processing
- Medical imaging
- Satellite imagery analysis
Problems Solved
This technology helps in:
- Enhancing image quality
- Improving image resolution
- Removing noise from images
Benefits
The benefits of this technology include:
- Better image quality
- Enhanced image resolution
- Noise reduction in images
Potential Commercial Applications
Potential commercial applications of this technology could be in:
- Photography software
- Medical imaging devices
- Satellite imaging companies
Possible Prior Art
One possible prior art for this technology could be:
- Image upscaling algorithms
- Image denoising techniques
What are the specific neural networks used in this technology?
The specific neural networks used in this technology are not mentioned in the abstract. Further details about the neural networks and their architecture would provide a better understanding of the innovation.
How does this technology compare to existing image upscaling methods?
The comparison of this technology with existing image upscaling methods is not discussed in the abstract. Understanding the unique features and advantages of this technology over traditional upscaling methods would be beneficial for evaluating its effectiveness.
Original Abstract Submitted
apparatuses, systems, and techniques to use one or more neural networks to generate an upsampled version of one or more images based, at least in part, on a denoised version of said one or more images. at least one embodiment pertains to generating an upsampled high-resolution image from a noisy version and denoised version of a low-resolution image. at least one embodiment pertains to separating components of a low-resolution image before denoising an image.
