| CPC G06N 3/045 (2023.01) [G06V 10/82 (2022.01)] | 8 Claims |
|
1. An information processing device, comprising:
a parallel deep neural network configured to input a captured image of an article to deep neural network models respectively corresponding to a plurality of articles and perform inferences about the plurality of articles in parallel using the deep neural network models;
a new article determination unit configured to determine whether an article included in the image is an unlearned article based on learned model information about the articles and the image; and
a new article learning unit configured to learn a deep neural network model corresponding to the article determined to be unlearned based on the image and initial model configuration information about the deep neural network model when the article included in the image is determined to be an unlearned article; and
a shape detection unit configured to detect a shape of the article from the image,
wherein the new article learning unit adds the learned deep neural network model to the deep neural network models,
wherein the new article learning unit learns the deep neural network model corresponding to the article included in the image based on configuration information indicating a feature corresponding to the detected shape of the article, and
wherein the parallel deep neural network includes:
a feature extraction unit configured to extract a feature from the image, and
an identification unit configured to output a confidence value indicating a probability that an article corresponding to the deep neural network model exists based on the extracted feature, and
wherein the feature extraction unit is shared for each detected shape of the article.
|