An electronic device is provided. The electronic device includes a camera module, a communication circuit, a memory, and a processor, wherein the processor may execute a first application using the camera module, obtain a first image through the camera module while the first application operates, recognize an object of a specified type in the first image, obtain location information of where the first image is obtained, determine a first virtual point corresponding to the location information on a three-dimensional (3D) virtual map, obtain a second image corresponding to the first image at the first virtual point, and update data of the 3D virtual map on the object based on a comparison between the first image and the second image.

Methods, systems, and apparatus, including medium-encoded computer program products, for a secure edge platform that uses image classification machine learning models. An edge platform can include at least one camera and can identify image classification models that generate classification output data from image data generated by the cameras. The edge platform can receive image data generated by the camera, and provide the image data to the models. In response to providing the image data classification models, the edge platform can receive classification output data. In response to receiving the classification output data from the image classification models, the edge platform can generate augmentation data that is associated with the image data, then transmit detection data to a central server platform. The detection data can include (i) the classification output data and (ii) the augmentation data associated with the image data. Data can be made recordable, reportable, searchable, and alarmable.

Based on the identification number of completely wireless earphones entered into an input unit, a checking unit of a terminal device checks whether or not conditions regarding an expiration period and the number of times of use for an exchange service for exchanging one of the pair that is not lost with left and right earphones are satisfied. A display control unit causes a display unit to display a message with an instruction to return the earphone that is not lost when the conditions are satisfied.

Based on the identification number of completely wireless earphones entered into an input unit, a checking unit of a terminal device checks whether or not conditions regarding an expiration period and the number of times of use for an exchange service for exchanging one of the pair that is not lost with left and right earphones are satisfied. A display control unit causes a display unit to display a message with an instruction to return the earphone that is not lost when the conditions are satisfied.

Systems and methods of image searching include receiving content, receiving a request to select an image from content, selecting a plurality of items in the image, retrieving information about the selected item, and providing display data based on the retrieved information.

A laundry data analysis apparatus based on artificial intelligence according to an embodiment of the present invention includes: a communication unit configured to receive an image including laundry data related to characteristics of laundry from an image acquisition device corresponding to a group including at least one member; and a processor configured to recognize the laundry data from the received image, acquire additional data related to the characteristics of the laundry on the basis of the recognized laundry data, store laundry information including the laundry data and the additional data into a database, and acquire member characteristic information of each of the at least one member from a plurality of laundry information corresponding to the group stored in the database.

Techniques for sanitizing personally identifiable information (PII) from audio and visual data are provided. For instance, in a scenario where the data comprises an audio signal with speech uttered by a person P, these techniques can include removing/obfuscating/transforming speech-related PII in the audio signal such as pitch and acoustic cues associated with P's vocal tract shape and/or vocal actuators (e.g., lips, nasal air bypass, teeth, tongue, etc.) while allowing the content of the speech to remain recognizable. Further, in a scenario where the data comprises a still image or video in which a person P appears, these techniques can include removing/obfuscating/transforming visual PII in the image or video such as P's biological features and indicators of P's location/belongings/data while allowing the general nature of the image or video to remain discernable. Through this PII sanitization process, the privacy of individuals portrayed in the audio or visual data can be preserved.

An image detection method determines a target object. A plurality of original images of a scene in front of a vehicle are obtained. An object in one original image is detected, and a degree of similarity between the object in the original image and the target object in a preset image is calculated. If the degree of similarity is greater than a preset similarity threshold, it is determined that the original image is a target image and the object is the target object. A position of the target object relative to the vehicle is determined and output. The method can recognize objects of interest in front of a driver.

An image detection method determines a target object. A plurality of original images of a scene in front of a vehicle are obtained. An object in one original image is detected, and a degree of similarity between the object in the original image and the target object in a preset image is calculated. If the degree of similarity is greater than a preset similarity threshold, it is determined that the original image is a target image and the object is the target object. A position of the target object relative to the vehicle is determined and output. The method can recognize objects of interest in front of a driver.

A medical device monitoring system and method extract information from screen images from medical device controllers, with a single OCR process invocation per screen image, despite critical information appearing in different screen locations, depending on which medical device controller's screen image is processed. For example, different software versions of the medical device controllers might display the same type of information in different screen locations. Copies of the critical screen information, one copy from each different screen location, are made in a mosaic image, and then the mosaic image is OCR processed to produce text results. Text is selectively extracted from the OCR text results, depending on contents of a selector field on the screen image, such as a software version number or a heart pump model identifier.