18382128. STATE DETERMINATION APPARATUS USING MACHINE LEARNING MODEL, DETERMINATION METHOD, AND STORAGE MEDIUM simplified abstract (NEC Corporation)

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STATE DETERMINATION APPARATUS USING MACHINE LEARNING MODEL, DETERMINATION METHOD, AND STORAGE MEDIUM

Organization Name

NEC Corporation

Inventor(s)

Eiji Yumoto of Tokyo (JP)

Masahiro Hayashitani of Tokyo (JP)

Takeshi Hasegawa of Tokyo (JP)

Yuji Kosaka of Tokyo (JP)

STATE DETERMINATION APPARATUS USING MACHINE LEARNING MODEL, DETERMINATION METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18382128 titled 'STATE DETERMINATION APPARATUS USING MACHINE LEARNING MODEL, DETERMINATION METHOD, AND STORAGE MEDIUM

Simplified Explanation

The patent application describes a state determination apparatus that accurately determines if a target is in a specific state by calculating a score based on data obtained from the target, setting a threshold based on the data, and comparing the score to the threshold.

  • Calculation section calculates a score indicating the degree to which the target is in the specific state.
  • Decision section determines a threshold based on the data.
  • Determination section compares the score to the threshold to determine if the target is in the specific state.

Potential Applications

This technology can be applied in various fields such as:

  • Medical diagnosis
  • Quality control in manufacturing
  • Environmental monitoring

Problems Solved

The technology addresses the following issues:

  • Accurately determining the state of a target
  • Improving decision-making based on data analysis

Benefits

The benefits of this technology include:

  • High accuracy in determining the state of a target
  • Efficient decision-making process
  • Potential for automation in various industries


Original Abstract Submitted

In order to achieve an object to determine, with high accuracy, that a target is in a specific state, a state determination apparatus includes: a calculation section that calculates, on the basis of data obtained from the target, a score indicative of a degree to which the target is in the specific state; a decision section that decides a threshold on the basis of the data; and a determination section that determines, by comparing the score and the threshold, whether the target is in the specific state.