Abstract: Embodiments of the disclosure provide an image processing method and apparatus, a computer-readable medium, and an electronic device. The image processing method includes: extracting a feature map of a target image; dividing the feature map into target regions; determining weights of the target regions according to feature vectors of the target regions; and generating a feature vector of the target image according to the weights of the target regions and the feature vectors of the target regions.

Abstract: A data processing method includes: generating a service serial number for a target service according to a preset naming rule; obtaining service data of the target service; obtaining a target data table from a plurality of pre-configured data tables, according to the service serial number; and storing the service data to the target data table.

Abstract: In some examples, a database system receives data relating to plural micro-models that apply respective analytics, and distributes a plurality of data segments of the received data across the plurality of processing engines based on values of a segmentation key included in the received data. A plurality of processing engines, performs in parallel, operations associated with the plural micro-models using respective data segments of the plurality of data segments, where different processing engines of the plurality of processing engines perform operations associated with respective micro-models of the plural micro-models.

Abstract: Object monitoring methods and apparatuses, electronic devices, and computer readable storage media are provided. The object monitoring method includes: acquiring WiFi data of a current location of a target object; comparing the WiFi data of the current location with a target location WiFi data list; and in response to a match between the WiFi data of the current location and an item in the target location WiFi data list, generating and reporting target location WiFi monitoring data.

Abstract: In some examples, a database system receives data relating to plural micro-models that apply respective analytics, and distributes a plurality of data segments of the received data across the plurality of processing engines based on values of a segmentation key included in the received data. A plurality of processing engines, performs in parallel, operations associated with the plural micro-models using respective data segments of the plurality of data segments, where different processing engines of the plurality of processing engines perform operations associated with respective micro-models of the plural micro-models.

Abstract: Embodiments of the disclosure provide an image processing method and apparatus, a computer-readable medium, and an electronic device. The image processing method includes: extracting a feature map of a target image; dividing the feature map into target regions; determining weights of the target regions according to feature vectors of the target regions; and generating a feature vector of the target image according to the weights of the target regions and the feature vectors of the target regions.

Abstract: Provided is a method including: receiving an audio signal of a transmitter; detecting sensitive information in the audio signal based on content of the audio signal; encrypting the sensitive information by using characteristic information of a receiver; and transmitting the audio signal including the encrypted sensitive information.

Abstract: Provided is a method including: receiving an audio signal of a transmitter; detecting sensitive information in the audio signal based on content of the audio signal; encrypting the sensitive information by using characteristic information of a receiver; and transmitting the audio signal including the encrypted sensitive information.

Abstract: A text editing apparatus includes: a display configured to display text; a user input unit configured to receive a speech signal for editing the text; and a controller configured to analyze a meaning of a word included in the speech signal, determine an editing target and an editing type, edit the text based on the determined editing target and editing type, and display the edited text on the display.

Abstract: A method for speech command detection comprises extracting speech features from a speech signal inputted into a system, converting the speech features into a word sequence, obtaining time durations of speech segments corresponding to the respective non-command words and an acoustic score of each of the command word candidates, calculating rhythm features of the speech signal based on the time durations, and recognizing a speech corresponding to the at least one command word candidates as a speech command directed to the system or a speech not directed to the system based on the acoustic score and the rhythm features. The word sequence comprises at least two successive non-command words and at least one command word candidate. The rhythm features describe a similarity of time durations of speech segments corresponding to the respective non-command words, and/or a similarity of energy variations of the speech segments corresponding to the respective non-command words.

Abstract: A command recognition device includes: an utterance understanding unit that determines or selects word sequence information from speech information; speech confidence degree calculating unit that calculates degree of speech confidence based on the speech information and the word sequence information; a phrase confidence degree calculating unit that calculates a degree of phrase confidence based on image information and phrase information included in the word sequence information; and a motion control instructing unit that determines whether a command of the word sequence information should be executed based on the degree of speech confidence and the degree of phrase confidence.

Abstract: A command recognition device includes: an utterance understanding unit that determines or selects word sequence information from speech information; speech confidence degree calculating unit that calculates degree of speech confidence based on the speech information and the word sequence information; a phrase confidence degree calculating unit that calculates a degree of phrase confidence based on image information and phrase information included in the word sequence information; and a motion control instructing unit that determines whether a command of the word sequence information should be executed based on the degree of speech confidence and the degree of phrase confidence.