Learning apparatus, inference apparatus, inference system, learning method, inference method, and non-transitory computer-readable storage medium

A learning apparatus comprising:

• one or more processors;
• and
• one or more memories storing executable instructions which, when executed by the one or more processors, cause the learning apparatus to function as:
• a first acquisition unit configured to acquire at least one pair of an image and a label;
• a first calculation unit configured to calculate a feature vector from the image using a feature extractor;
• a second calculation unit configured to calculate, as a positive pair similarity, a similarity between a first feature vector calculated by the first calculation unit from the image acquired by the first acquisition unit and a second feature vector associated with the same label as the label acquired by the first acquisition unit, and calculate, as a negative pair similarity, a similarity between the first feature vector calculated by the first calculation unit from the image acquired by the first acquisition unit and a third feature vector associated with a label different from the label acquired by the first acquisition unit;
• a decision unit configured to decide a similarity threshold;
• a third calculation unit configured to calculate a loss value with respect to the positive pair similarity lower than the threshold;
• a fourth calculation unit configured to calculate a loss value with respect to the negative pair similarity higher than the threshold;
• and
• a learning unit configured to learn a parameter of the feature extractor that decreases the loss value calculated by the third calculation unit and the loss value calculated by the fourth calculation unit,
• wherein one of the third calculation unit and the fourth calculation unit uses a loss function including a function such that an absolute value of a gradient is larger near a predetermined threshold and is non-zero but smaller even at a point away from the threshold.