KYOCERA Document Solutions Inc. (20240330670). MACHINE LEARNING PREFLIGHT PRINTING SYSTEM AND METHODS simplified abstract

MACHINE LEARNING PREFLIGHT PRINTING SYSTEM AND METHODS

Organization Name

KYOCERA Document Solutions Inc.

Inventor(s)

Javier A. Morales of Rochester NY (US)

Matthew Morikawa of Concord CA (US)

MACHINE LEARNING PREFLIGHT PRINTING SYSTEM AND METHODS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240330670 titled 'MACHINE LEARNING PREFLIGHT PRINTING SYSTEM AND METHODS

Simplified Explanation:

The patent application describes a printing system that includes a preflight system using a generative adversarial network to identify potential errors in print jobs before printing.

• The printing system includes a printing device and a preflight system.
• The preflight system checks incoming print jobs for errors before printing.
• A generative adversarial network is used to identify possible printing issues.
• The network consists of a generative neural network and a discriminatory neural network.
• The generative neural network introduces errors into data to train the discriminatory network.
• The discriminatory network backpropagates its output to train the generative network.

Key Features and Innovation:

• Printing system with preflight system for error checking.
• Use of generative adversarial network for identifying printing issues.
• Training process between generative and discriminatory neural networks.

Potential Applications:

• Commercial printing operations.
• Graphic design and printing services.
• Quality control in printing industry.

Problems Solved:

• Identifying errors in print jobs before printing.
• Improving print job accuracy and quality.
• Enhancing efficiency in printing processes.

Benefits:

• Reduced printing errors and waste.
• Improved print job quality and accuracy.
• Streamlined printing operations.

Commercial Applications:

Preflight systems using generative adversarial networks can revolutionize the printing industry by significantly reducing errors and improving print job quality. This technology can be applied in commercial printing operations, graphic design services, and various other industries that rely on accurate and high-quality printing.

Questions about Printing Preflight Systems using Generative Adversarial Networks:

1. How does the generative adversarial network in the preflight system improve the accuracy of print jobs? 2. What are the potential cost-saving benefits of implementing this technology in commercial printing operations?

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Original Abstract Submitted

a printing system includes a printing device. the printing system also includes a preflight system that checks incoming print jobs for possible errors or issues before commencing printing operations. the preflight system implements a generative adversarial network to facilitate the identification of possible problems with printing. the generative adversarial network includes a generative neural network and a discriminatory neural network. the generative neural network introduces errors into input data to train the discriminatory neural network in identifying problems with print jobs. the discriminatory neural network backpropagates its output to train the generative neural network.