18375648. ARITHMETIC OPERATION SYSTEM, TRAINING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING TRAINING PROGRAM simplified abstract (NEC Corporation)
Contents
- 1 ARITHMETIC OPERATION SYSTEM, TRAINING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING TRAINING PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ARITHMETIC OPERATION SYSTEM, TRAINING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING TRAINING PROGRAM - 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
ARITHMETIC OPERATION SYSTEM, TRAINING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING TRAINING PROGRAM
Organization Name
Inventor(s)
Tsubasa Nakamura of Tokyo (JP)
ARITHMETIC OPERATION SYSTEM, TRAINING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING TRAINING PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18375648 titled 'ARITHMETIC OPERATION SYSTEM, TRAINING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM STORING TRAINING PROGRAM
Simplified Explanation
The patent application describes a system where an evaluation unit calculates the difference between a teaching signal and an estimated signal. The teaching signal is obtained by integrating spatial distribution signals observed by a sensor using emission waves for a spatial structure along a region of interest in an emission wave region. The estimated signal is calculated by integrating estimated density of sample points obtained from a spatial estimation model.
- Evaluation unit calculates difference between teaching signal and estimated signal
- Teaching signal obtained by integrating spatial distribution signals observed by a sensor using emission waves
- Estimated signal calculated by integrating estimated density of sample points from a spatial estimation model
Potential Applications
This technology could be applied in various fields such as:
- Remote sensing
- Environmental monitoring
- Medical imaging
Problems Solved
This technology helps in:
- Improving accuracy of signal estimation
- Enhancing spatial distribution analysis
Benefits
The benefits of this technology include:
- Increased precision in signal calculation
- Better understanding of spatial structures
Potential Commercial Applications
This technology could be commercially benefit:
- Companies involved in remote sensing technology
- Healthcare industry for medical imaging advancements
Possible Prior Art
One possible prior art for this technology could be:
- Spatial estimation models used in remote sensing applications
What are the specific emission waves used in this system?
The specific emission waves used in this system are not mentioned in the abstract. It would be helpful to know the exact type of emission waves utilized for the spatial structure integration.
How does the sampling unit input information about the position of sample points?
The abstract does not elaborate on how the sampling unit inputs information about the position of sample points to the spatial estimation model. Understanding this process in more detail could provide insights into the functioning of the system.
Original Abstract Submitted
In an arithmetic operation system, an evaluation unit calculates a difference amount between a teaching signal and an estimated signal. The teaching signal has a value that is obtained by integrating spatial distribution signals observed by a sensor using emission waves for a spatial structure along a region of interest in an emission wave region in which emission waves are emitted from a plurality of emission reference directions and reach the sensor. The region of interest is a curved line region or a curved surface region intersecting the plurality of emission reference directions. This estimated signal is calculated by integrating a plurality of pieces of estimated density of a plurality of sample points obtained from a spatial estimation model by having a sampling unit input information about a position of each of the plurality of sample points on the region of interest to the spatial estimation model.
