US 2023/0419114 A1 · ELECTRONIC APPARATUS AND CONTROL METHOD THEREOF

Abstract

An electronic apparatus is provided. The electronic apparatus includes a memory and a processor, wherein the processor is configured to, by executing the at least one instruction, acquire a plurality of training data; acquire a plurality of embedding vectors that are mappable to an embedding space for the plurality of training data, respectively; train an artificial intelligence model classifying the plurality of training data based on the plurality of embedding vectors, identify an embedding vector misclassified by the artificial intelligence model among the plurality of embedding vectors, identify an embedding vector closest to the misclassified embedding vector in the embedding space, acquire a synthetic embedding vector corresponding to a path connecting the misclassified embedding vector to the embedding vector closest to the misclassified embedding vector in the embedding space, and re-train the artificial intelligence model by adding the synthetic embedding vector to the training data.

Claims18

Dependent claims

An electronic apparatus comprising:

a memory storing at least one instruction;
and
a processor connected to the memory to control the electronic apparatus,
wherein, by executing the at least one instruction, the processor is configured to:
acquire training data comprising a plurality of pieces of training data;
based on the training data, acquire a plurality of embedding vectors that are mappable to an embedding space for the plurality of pieces of training data, respectively;
based on the plurality of embedding vectors, train an artificial intelligence model classifying the plurality of pieces of training data;
identify a misclassified embedding vector misclassified by the artificial intelligence model among the plurality of embedding vectors;
identify an embedding vector closest to the misclassified embedding vector in the embedding space;
acquire a synthetic embedding vector corresponding to a path connecting the misclassified embedding vector to the embedding vector closest to the misclassified embedding vector in the embedding space;
and
re-train the artificial intelligence model by adding the synthetic embedding vector to the training data.

9 more elements

A non-transitory computer-readable recording medium including a program for executing a control method of an electronic apparatus, the control method comprising:

acquiring training data comprising a plurality of pieces of training data;
based on the training data, acquiring a plurality of embedding vectors that are mappable to an embedding space for the plurality of pieces of training data, respectively;
based on the plurality of embedding vectors, training an artificial intelligence model classifying the plurality of pieces of training data;
identifying a misclassified embedding vector misclassified by the artificial intelligence model among the plurality of embedding vectors;
identifying an embedding vector closest to the misclassified embedding vector in the embedding space;
acquiring a synthetic embedding vector corresponding to a path connecting the misclassified embedding vector to the embedding vector closest to the misclassified embedding vector in the embedding space;
and
re-training the artificial intelligence model by adding the synthetic embedding vector to the training data.

5 more elements

Dependencies are inferred from the claim text.

Electronic apparatus and control method thereof

Life of this patent

Electronic apparatus and control method thereof

Life of this patent

Abstract

Claims18