Abstract:
An embodiment of the present invention provides, comprising: a communication unit configured to communicate with a plurality of external AI apparatuses; and a processor configured to receive sound signals of the user from the plurality of external AI apparatuses, calculate a distance and a variation of the distance from each of the plurality of external AI apparatuses to the user based on the received sound signals, determine a current path of the user based on the calculated distance and the calculated variation of the distance, and determine a future path of the user based on the current path.
Abstract:
An artificial intelligence server is disclosed. The artificial intelligence server includes an input unit to which input data is inputted, and a processor, when a first output value outputted by an artificial intelligence model with respect to first input data is correct and a second output value outputted by the artificial intelligence model with respect to second input data is incorrect, configured to use the first input data and the second input data to obtain a first domain causing an incorrect answer, and train the artificial intelligence model to be domain-adapted for the first domain.
Abstract:
Disclosed is an artificial intelligence server. The artificial intelligence server includes a communicator in communication with at least one electronic device and a processor for receiving input data from a specific electronic device, applying personalized information corresponding to the specific electronic device to a recognition model, inputting the input data into the recognition model to which the personalized information is applied to obtain a final result value, and transmitting the final result value to the specific electronic device.
Abstract:
An AI device is provided. The AI device includes a memory to store data, a voice acquisition interface to acquire a voice signal, and a processor to perform preprocessing for the voice signal based on a parameter, to provide the preprocessed voice signal to a voice recognition model, to acquire a voice recognition result, to store a characteristic of the preprocessed voice signal in the memory, and to change the parameter using a distribution of characteristics of voice signals accumulated in the memory.
Abstract:
A stereo camera and a driver assistance apparatus and a vehicle including the same are disclosed. The stereo camera includes a first image sensor to sense an image corresponding to at least one exposure time, a second image sensor to sense images corresponding to a plurality of exposure times, and a processor to generate a disparity map and an RGB image based on the images acquired by the first and second image sensors. Consequently, it is possible to acquire the disparity map and the RGB image.
Abstract:
An embodiment of the present invention provides an AI apparatus comprising: a communication unit configured to communicate with a plurality of external AI apparatuses; and a processor configured to: receive sound signals of the user from the plurality of external AI apparatus, calculate a distance and a variation of the distance from each of the plurality of external AI apparatus to the user based on the obtained sound signals, determine a current path of the user based on the calculated distance and the calculated variation of the distance, and determine a future path of the user based on the current path.
Abstract:
Disclosed herein is an artificial intelligence server for updating an artificial intelligence model by merging a plurality of pieces of update information including a memory configured to store a first artificial intelligence model, a communication modem configured to communicate with a plurality of artificial intelligence apparatuses, and a processor configured to transmit the first artificial intelligence model to the plurality of artificial intelligence apparatuses, receive, from at least one of the plurality of artificial intelligence apparatuses, first update information of the first artificial intelligence model or second update information of a second artificial intelligence model updated from the first artificial intelligence model, select third update information to be used to update the first artificial intelligence model from the first update information and the second update information, and update the first artificial intelligence model using the third update information.
Abstract:
An embodiment of the present disclosure provides an artificial intelligence apparatus for generating training data including a memory configured to store an artificial intelligence model, an input interface including a microphone or a camera, and a processor configured to receive, via the input interface, input data, generate an inference result corresponding to the input data by using the artificial intelligence model, receive feedback corresponding to the inference result, determine suitability of the input data and the feedback for updating the artificial intelligence model, and generate training data based on the input data and the feedback if the input data and the feedback are determined as data suitable for updating of the artificial intelligence model.
Abstract:
An artificial intelligence device according to an embodiment of the present invention may include a microphone configured to receive voice; a sound output unit configured to output sound; an artificial intelligence unit configured to acquire context information of a target, based on at least one of an image received from a camera disposed outside and a voice received from the microphone, generate feedback information according to the acquired context information, and determine output volume intensity of the generated feedback information; and a controller configured to control the sound output unit to output the feedback information at the determined output volume intensity.
Abstract:
An artificial intelligence apparatus for recognizing a user includes a camera, and a process configured to receive, via the camera, image data including a recognition target object, generate recognition information corresponding to the recognition target object from the received image data, calculate a confidence level of the generated recognition information, determine whether the calculated confidence level is greater than a reference value, if the calculated confidence level is greater than the reference value, perform a control corresponding to the generated recognition information, and if the calculated confidence level is not greater than the reference value, provide a feedback for the object recognition.