CPC G06F 21/6245 (2013.01) [G06F 16/55 (2019.01); G06F 16/5846 (2019.01); G06F 16/587 (2019.01); G06F 21/10 (2013.01); G06N 3/08 (2013.01)] | 12 Claims |
1. An electronic device, comprising:
a memory comprising a neural network model trained to identify private information of a user of the electronic device comprised in an image;
a display;
a communicator comprising circuitry; and
a processor configured to:
based on a user command to transmit a first image to an external device being input, identify whether the private information of the user is comprised in the first image by inputting the first image in the neural network model,
based on identifying that the private information of the user is comprised in the first image, control the display to display a first user interface (UI) asking whether to process at least one piece of the private information based on the private information comprised in the first image, and
based on a user command input through the first UI, process the first image and control the communicator to transmit the processed first image to the external device,
wherein the neural network model comprises:
an object detection model trained to detect one or more objects comprised in the first image and classify a detected object as at least one of text or an image;
a text classification model trained to output a first privacy level corresponding to an object classified as the text from among detected objects; and
an image classification model trained to output a second privacy level corresponding to an object classified as the image from among the detected objects,
wherein the processor is further configured to:
based on the first privacy level exceeding a first threshold value or the second privacy level exceeding a second threshold value which is different from the first threshold value, identify that the private information of the user is comprised in the first image, and
obtain meta data on the private information comprised in the first image through the neural network model, and
wherein the text classification model comprises a text type classification model which is trained to output the first privacy level corresponding to a text type based on the text type obtained through a rule-based classification model and final feature data obtained through a feature data processing model.
|