Information processing device, information processing method, and a non-transitory computer readable recording medium including selecting a base image including a target region with an object subject to machine learning and for combination with another target region in another image to include in a dataset for training a machine learning model

An information processing method comprising:

• selecting a base image from a base dataset that is a set of images including a target region including an object to be subjected to machine learning and a background region not including an object to be subjected to machine learning, and generating a processing target image that is a copy of the selected base image;
• selecting the target region included in another image included in the base dataset;
• combining an image of the selected target region and information on an object to be subjected to machine learning included in the image of the target region with the processing target image;
• generating a dataset that is a set of the processing target images obtained by combining a predetermined number of the target regions;
• calculating a feature of an image included in the dataset;
• generating a learned model using first machine learning that is machine learning using the feature and the dataset;
• outputting the generated learned model;
• executing third machine learning that is machine learning using the dataset but does not reuse the feature;
• determining the feature to be reused using a result of profiling of an execution status of the third machine learning;
• executing the first machine learning using the determined feature and the dataset;
• and
• determining which output of a layer in a neural network is used as the feature to be reused using a result of profiling.

A non-transitory computer-readable recording medium embodying a program, the program causing a computer to perform a method, the method comprising:

• selecting a base image from a base dataset that is a set of images including a target region including an object to be subjected to machine learning and a background region not including an object to be subjected to machine learning, and generating a processing target image that is a copy of the selected base image;
• selecting the target region included in another image included in the base dataset;
• combining an image of the selected target region and information on an object to be subjected to machine learning included in the image of the target region with the processing target image;
• generating a dataset that is a set of the processing target images obtained by combining a predetermined number of the target regions;
• calculating a feature of an image included in the dataset;
• generating a learned model using first machine learning that is machine learning using the feature and the dataset;
• outputting the generated learned model;
• executing third machine learning that is machine learning using the dataset but does not reuse the feature;
• determining the feature to be reused using a result of profiling of an execution status of the third machine learning;
• executing the first machine learning using the determined feature and the dataset;
• and
• determining which output of a layer in a neural network is used as the feature to be reused using a result of profiling.