Abstract:
An apparatus for discriminating a disguised face includes a face area detector configured to detect a face area in an input image provided from an external source. The apparatus includes a skin color modeling module configured to separate a skin color area from the face area and a disguised face discriminator configured to determine whether signals in the skin color area have a pulse component to discriminate whether a face in the input image is the disguised face.
Abstract:
Disclosed herein a method and apparatus for recommending a table service based on image recognition. According to an embodiment of the present disclosure, there is provided a method for recommending a table service, including: receiving a table image that is captured in real time; acquiring, by using an artificial intelligence of a pre-learned learning model, table information that includes object information and food information of at least one table in the table image; and recommending, based on the table information, a service for each of the at least one table.
Abstract:
Disclosed herein a method and apparatus for learning a locally-adaptive local device task based on cloud simulation. According to an embodiment of the present disclosure, there is provided a method for learning a locally-adaptive local device task. The method comprising: receiving observation data about a surrounding environment recognized by a local device; performing a domain randomization based on the observation data and a failure type of a task assigned to the local device and relearning a policy network of the assigned task based on the domain randomization; and updating a policy network of the local device for the assigned task by transmitting the relearned policy network to the local device.
Abstract:
A method includes matching a pupil center position obtained from image information taken by a camera and a center position of an UI on a display panel of a terminal, and recognizing the match as a touch on the UI when the match between the pupil center position and the center position of the UI is kept for a predetermined time or more.
Abstract:
Provided is a multiple-intelligence detection system. The multiple-intelligence detection system includes an image detection device obtaining image information for evaluating multiple-intelligence from a user, a multiple-intelligence measurement model unit receiving the image information from the image detection device to perform multiple-intelligence evaluation through selection of one of a first reaction and a second reaction, and a content unit receiving a result of the evaluated multiple-intelligence from the multiple-intelligence measurement model unit to generate an individual portfolio on the basis of the received result. The multiple-intelligence measurement model unit selects one of the first and second reactions on the basis of a reference reaction according to feelings and behavior patterns of the user.