18584967. INFORMATION PROCESSING APPARATUS, METHOD, AND PROGRAM simplified abstract (FUJIFILM Corporation)
Contents
INFORMATION PROCESSING APPARATUS, METHOD, AND PROGRAM
Organization Name
Inventor(s)
Akimichi Ichinose of Tokyo (JP)
INFORMATION PROCESSING APPARATUS, METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18584967 titled 'INFORMATION PROCESSING APPARATUS, METHOD, AND PROGRAM
Simplified Explanation: The patent application describes a processor that uses a trained neural network to evaluate properties of a structure in an image, corrects property scores based on relationships between the properties, and provides discrimination results for the structure.
Key Features and Innovation:
- Processor utilizes a trained neural network to assess property scores for predetermined property items in an image.
- Corrects property scores by analyzing relationships between the property items.
- Derives discrimination results for the structure based on corrected property scores.
Potential Applications: This technology can be applied in various fields such as image analysis, quality control in manufacturing, and structural assessment in engineering.
Problems Solved:
- Provides a more accurate evaluation of properties in a structure.
- Enhances the understanding of relationships between different properties.
- Improves discrimination results for structures based on property assessments.
Benefits:
- Increased accuracy in property evaluation.
- Enhanced understanding of property relationships.
- Improved discrimination results for structures.
Commercial Applications: The technology can be used in industries such as construction, manufacturing, and healthcare for quality control, structural analysis, and image processing applications.
Prior Art: Further research can be conducted in the fields of neural networks, image processing, and property assessment technologies to explore related prior art.
Frequently Updated Research: Stay updated on advancements in neural networks, image analysis, and property assessment technologies to enhance the application of this innovation.
Questions about the Technology: 1. What are the potential limitations of using a trained neural network for property assessment in images? 2. How can the correction of property scores based on relationships between properties improve the accuracy of discrimination results?
Original Abstract Submitted
A processor uses a trained neural network to derive a property score for each of a plurality of predetermined property items regarding a structure of interest included in an image; corrects a property score for at least one property item among the plurality of property items by referring to information indicating a relationship between the plurality of property items, the information being derived by analyzing a co-occurrence relationship between descriptions of properties included in a plurality of sentences; and derives a discrimination result for the plurality of property items regarding the structure of interest based on the corrected property score.
