US Patent Application 18013802. Machine Learning for High Quality Image Processing simplified abstract
Contents
Machine Learning for High Quality Image Processing
Organization Name
Inventor(s)
Noritsugu Kanazawa of Campbell CA (US)
Machine Learning for High Quality Image Processing - A simplified explanation of the abstract
This abstract first appeared for US patent application 18013802 titled 'Machine Learning for High Quality Image Processing
Simplified Explanation
- The patent application describes a system or method for inpainting, which is the process of filling in missing or damaged parts of an image. - The system or method uses machine learning and ground truth data training to improve the efficiency and accuracy of inpainting. - By training machine-learning models with ground truth image data, the inpainting process can be more precise and effective. - The machine-learning models can predict and inpaint various types of data, making them versatile and applicable in different scenarios. - The trained models can make predictions without the need for ground truth reassurance, thanks to calibrated parameters obtained through the training process.
Original Abstract Submitted
A system or method for inpainting can be aided through the use of machine learning and ground truth data training. The training of machine-learning inpainting models through the use of ground truth image data may add efficiency and precision to the field of image inpainting. Furthermore, machine-learning inpainting models can aid in the non-deterministic prediction of a variety of data types and can be applicable to the removing and/or replacing of a variety of data types. The trained models can be enabled to make predictions without ground truth reassurance due to calibrated parameters tuned through the training.
