18228832. INFORMATION PROCESSING METHOD simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)

INFORMATION PROCESSING METHOD

Organization Name

TOYOTA JIDOSHA KABUSHIKI KAISHA

Inventor(s)

Mitsuhiro Mabuchi of Edogawa-ku Tokyo-to (JP)

INFORMATION PROCESSING METHOD - A simplified explanation of the abstract

This abstract first appeared for US patent application 18228832 titled 'INFORMATION PROCESSING METHOD

Simplified Explanation

The information processing method described in the patent application involves generating a learned model for image recognition by combining multiple first models with a second model that is different from the first models.

• Dividing an image into patches for learning purposes.
• Inputting each patch into a respective first model for calculation.
• Combining the output of the first models in the second model to generate a learned model.

• • Potential Applications:**

- Image recognition software - Object detection systems - Facial recognition technology

• • Problems Solved:**

- Enhancing accuracy in image recognition - Improving performance of machine learning models - Streamlining the learning process for complex images

• • Benefits:**

- Increased efficiency in image recognition tasks - Enhanced accuracy in identifying objects within images - Improved overall performance of machine learning algorithms

Original Abstract Submitted

An information processing method generates a learned model for image recognition, wherein a learning model includes a plurality of first models and a second model that is different from the first models. The information processing method includes: dividing an image that is to be used in learning into a plurality of patches; inputting each of the divided plurality of patches into a respective model of the plurality of first models, the respective model being predetermined for each of the patches, and performing calculation; and combining an output of a calculation result of each of the plurality of first models in the second model and generating a learned model by learning the learning model.