Device that updates recognition model and method of updating recognition model

An information processing method executed by an information processing device comprising:

• estimating, using a category classification model learned based on learning data, a category of input image data input into the category classification model and a score representing confidence of the category;
• displaying an image representing the input image data and the estimated category with the score below a threshold value estimated by the category classification model of the input image data;
• accepting a correction of the displayed category from a user;
• and
• updating the category classification model to an updated category classification model by adding image data of a corrected category based on the correction accepted by the accepting step and the corrected category to the learning data and performing additional learning, wherein the updated category classification model outputs the corrected category when the image data of the corrected category is input.

A non-transitory computer-readable storage medium storing a program for causing a computer to perform an information processing method comprising:

• estimating, using a category classification model learned based on learning data, a category of input image data input into the category classification model and a score representing confidence of the category;
• displaying an image representing the input image data and the estimated category with the score below a threshold value estimated by the category classification model of the input image data;
• accepting a correction of the displayed category from a user;
• and
• updating the category classification model to an updated category classification model by adding image data of a corrected category based on the correction accepted by the accepting step and the corrected category to the learning data and performing additional learning, wherein the updated category classification model outputs the corrected category when the image data of the corrected category is input.

An image processing device comprising:

• one or more processors,
• wherein the one or more processors function as:
• an estimation unit configured to cause a category classification model learned based on learning data to output an estimated input image data input to the category classification model and a score representing confidence of the category, and to estimate the category of the input image data having the score that is equal to or greater than a first threshold value, as a first category, and to estimate the category of the input image data having the score less than a second threshold value, as a second category, wherein input image data not estimated as the first category or second category is determined as boundary image data;
• a display control unit configured to cause a display unit to display an image representing one or more boundary image data whose score is equal to or greater than the second threshold value and less than the first threshold value;
• an acceptance unit configured to accept category input for the displayed boundary image data from a user;
• and
• an updating unit configured to update the category classification model to an updated category classification model by adding the boundary image data and the corrected category accepted for the boundary image data by the acceptance unit to the learning data and performing additional learning, wherein the updated category classification model outputs the corrected category when the image data of the corrected category is input.