Abstract: A method, an apparatus, device and a storage medium for generating a target re-recognition model are provided. The method may include: acquiring a set of labeled samples, a set of unlabeled samples and an initialization model obtained through supervised training; performing feature extraction on each sample in the set of the unlabeled samples by using the initialization model; clustering features extracted from the set of the unlabeled samples by using a clustering algorithm; assigning, for each sample in the set of the unlabeled samples, a pseudo label to the sample according to a cluster corresponding to the sample in a feature space; and mixing a set of samples with a pseudo label and the set of the labeled samples as a set of training samples, and performing supervised training on the initialization model to obtain a target re-recognition model.

Abstract: A cloud computing resource extension method, a Smart Local Compute Cluster (SLCC), and a storage medium are suggested, which relate to the field of artificial intelligence. The method of cloud computing resource extension includes: acquiring registration information of an extended Availability Zone (AZ), the extended AZ being located in a user's local computer room; sending the registration information to a public cloud, the public cloud being configured to register, based on the registration information, the extended AZ with an AZ set managed and controlled by the public cloud and generate deployment information of a target cloud service pre-designated by the user; receiving the deployment information sent by the public cloud; and deploying the target cloud service in the extended AZ based on the deployment information.

Abstract: The present disclosure provides a method and apparatus for coupling a superconducting qubit. The method includes: determining a target coupling strength between a target read cavity and a qubit, a first target frequency of the qubit, and a second target frequency of the target read cavity; initializing a read coupling port configuration layout based on a configuration of the qubit, a relative position of the qubit to the target read cavity; calculating a to-be-measured coupling strength between the qubit and the read coupling port, based on the read coupling port configuration layout, the first target frequency, and the second target frequency; and in response to detecting that the to-be-measured coupling strength and the target coupling strength satisfy a preset condition, generating, based on the second target frequency and the read coupling port configuration layout, a complete layout comprising the qubit and the target read cavity.

Abstract: The present disclosure discloses a vehicle control method and apparatus, a device and a computer storage medium, and relates to the technical fields of autonomous driving and intelligent transportation. A specific implementation solution involves: determining vehicles in a preset geo-fencing region; determining a vehicle weight of each said vehicles according to a vehicle type and a waiting duration of each said vehicles; estimating, according to the vehicle weights of the vehicles in each of lanes in the geo-fencing region and positions of the vehicles in each said lanes, a duration to be waited in each said lanes; and generating a control instruction for each said vehicles according to the respective durations to be waited in each said lanes and the respective positions of the vehicles in each said lanes, the control instruction including a state instruction and/or a target speed instruction.

Abstract: The disclosure provides a method and a device for processing information, an electronic device, and a storage medium, belonging to a field of artificial intelligence including computer vision, deep learning, and natural language processing. In the method, the computing device recognizes multiple text items in the image. The computing device classifies multiple text items into a first set of name text items and a second set of content text items based on semantics of the text items. The computing device performs a matching operation between the first set and the second set based on a layout of the text items in the image, and determines matched name-content text items. The matched name-content text items include a name text item in the first set and a content text item matching the name text item and in the second set. The computing device outputs the matched name-content text items.

Abstract: Embodiments of the present disclosure provide methods and apparatuses for blockchain-based multi-party computation, a device and a medium, relate to blockchain technology in the field of computer technology. An embodiment of the method can include: encrypting business data, to obtain a ciphertext of the business data; hashing the ciphertext of the business data, to obtain a hash result of the business data; sending the hash result of the business data to a blockchain node, so that the blockchain node writes the hash result of the business data into a blockchain; and sending the ciphertext of the business data to a target trusted computing module in a target server, for instructing the target trusted computing module to perform multi-party computation based on the ciphertext of the business data and the hash result of the business data in the blockchain.

Abstract: The present disclosure provides a method for selecting an annotated sample. The method includes: determining a first attribute and a second attribute of a sample characteristic; in which the first attribute is a characteristic attribute of the sample characteristic in a source field sample set, and the second attribute is a characteristic attribute of the sample characteristic in a target field sample set; and determining a target annotated sample from a plurality of candidate annotated samples of the source field sample set according to the first attribute and the second attribute; in which the target annotated sample is configured to train a classification model, the classification model includes a model for determining an emotion polarity by analyzing an input sample to be classified.

Abstract: The disclosure provides a role labeling method. The method includes: obtaining a dialogue sentence to be labeled and context information corresponding to the dialogue sentence, and splicing the context information and the dialogue sentence to obtain a spliced text; extracting location information of a role name of the dialogue sentence in the spliced text from the spliced text; determining a first candidate role name of the dialogue sentence based on the location information; determining a second candidate role name of the dialogue sentence from role names in the spliced text; and determining a target role name of the dialogue sentence based on the first candidate role name and the second candidate role name, and performing role labeling on the dialogue sentence based on the target role name.

Abstract: Exemplary embodiments of the present disclosure provide a method and apparatus for managing a knowledge base, a device and a computer readable storage medium. The method for managing a knowledge base includes: forking, in response to receiving a request for modification of a rule for a first namespace, the rule to the first namespace, the rule being used to constrain structured data in a knowledge base; modifying, based on the request for modification of the rule, the rule in the first namespace; and adding the modified rule to a rule base associated with the knowledge base.

Abstract: The present disclosure provides a method and apparatus for processing a streaming media service, an electronic device, and a storage medium, and relates to the technical field of computers, particularly to technical fields such as industrial vision, deep learning, streaming media, and information flow. A specific implementation solution involves: acquiring registration information of an input source, the registration information including process information of a streaming media service process of the input source and streaming media address information of the input source; enabling the streaming media service process according to the process information; and controlling, by using the streaming media address information, the streaming media service process to process streaming media data of the input source.

Abstract: This application discloses a keyword generating method, an apparatus, a device and a storage medium, which relate to the field of natural language processing in the field of artificial intelligence. A specific implementation scheme includes: inputting a target text into a text processing model, obtaining a word sequence corresponding to the target text, and generating a semantic representation sequence corresponding to the word sequence; making prediction about each semantic representation vector in the semantic representation sequence respectively to obtain a prediction result; and if the prediction result indicates that a word corresponding to the semantic representation vector is capable of triggering a generation of a keyword, outputting the keyword based on the semantic representation vector and the prediction result. This method improves the accuracy of generating keywords.

Abstract: The present disclosure provides a method for training a linguistic model, related to fields of speech, natural language processing, deep learning technologies. A method includes: obtaining grammars corresponding to a plurality of sample texts and a slot value of a slot in each grammar by using semantic analysis; generating a grammar graph corresponding to each grammar based on the corresponding grammar and the slot value of the slot in the corresponding grammar; obtaining a weight of each grammar, a weight of each slot, and a weight of each slot value in each grammar graph based on the sample texts; determining at least one grammar frequency of each order based on the weight of each grammar, the weight of each slot, and the weight of each slot value in each grammar graph; and training the linguistic model based on the at least one grammar frequency of each order.

Abstract: An image recognition method, electronic device, and storage medium are provided and relate to the fields of artificial intelligence, computer vision, deep learning, image processing, and the like. The method includes: performing joint training on a first sub-network configured for recognition processing and a second sub-network configured for retrieval processing in a classification network by adopting an identical set of training data to obtain a trained target classification network, wherein, the first sub-network and the second sub-network are twin networks that are consistent in network structures and share a set of weights; and inputting image data to be recognized into the target classification network to obtain a recognition result. By adopting the method, the accuracy of the image recognition may be improved.

Abstract: A method and apparatus for evaluating a body feeling of a vehicle, an electronic device and a storage medium are provided. The method includes: a pressure of a measured object acting on each measurement region of a target riding apparatus under a current weight is measured by at least one pressure sensing unit within a measurement time period; a pressure intensity generated by the pressure of the measured object acting on each measurement region is calculated according to the pressure on each measurement region measured by each pressure sensing unit and an individual size of each pressure sensing unit; an objective body feeling evaluation score of the measured object under the current weight is determined according to the measured pressure and the calculated pressure intensity; and a comprehensive body feeling evaluation score is calculated according to the objective body feeling evaluation score and a predetermined subjective body feeling evaluation score.

Abstract: The present disclosure provides a landform map building method and apparatus, an electronic device and a readable storage medium, and relates to the field of image processing technologies.

Abstract: A method for recognizing a Chinese-English mixed speech, includes: determining pronunciation information and scores of a language model, of speech information, in response to receiving the speech information; determining whether an English word exists in content of the speech information based on the pronunciation information; determining a Chinese word corresponding to the English word based on a preset Chinese-English mapping table in response to the English word existing in the content of the speech information, in which the Chinese-English mapping table includes a mapping relationship of at least one pair of English word and Chinese word; determining a score of the Chinese word corresponding to the English word; replacing a score of the English word in the scores of the language model with the score of the Chinese word; and obtaining a speech recognition result for the speech information based on the replaced scores of the language model.

Abstract: Provided are an image processing method and apparatus, a device, and a storage medium, relating to the technical field of image processing, in particular to the artificial intelligence fields such as computer vision and deep learning. The specific implementation scheme is as follows: inputting a to-be-processed image into an encoding network to obtain a basic image feature, wherein the encoding network includes at least two cascaded overlapping encoding sub-networks which perform encoding and fusion processing on input data at at least two resolutions; and inputting the basic image feature into a decoding network to obtain a target image feature for pixel point classification, wherein the decoding network includes at least one cascaded overlapping decoding sub-network to perform decoding and fusion processing on input data at at least two resolutions respectively.

Abstract: The disclosure provides a speech control method, a speech control apparatus, an electronic device, and a storage medium. The method includes: acquiring target audio data sent by a client, the target audio data including audio data collected by the client within a target duration before wake-up and audio data collected by the client after wake-up; performing speech recognition on the target audio data; and controlling the client based on an instruction recognized from a second audio segment of the target audio data in response to recognizing a wake-up word from a first audio segment at beginning of the target audio data; in which, the second audio segment is later than the first audio segment or has an overlapping portion with the first audio segment.

Abstract: This application discloses a map display method and apparatus, where the method includes: obtaining an initial image, where a first road is included in the initial image. The initial image is divided into a first sub-image and a second sub-image, where the first road is not included in the first sub-image, and the first road is included in the second sub-image. The first sub-image is mapped to a first plane of a transition model, and the second sub-image is mapped to a second plane of the transition model, where there is an included angle between the first plane and the second plane, and the first plane is parallel to a screen of a display device. The second plane is controlled to move by means of the transition model, until the included angle is reduced from a first angle to a second angle, and a three-dimensional map display animation is obtained.

Abstract: The present disclosure discloses a method and apparatus for displaying map points of interest, and an electronic device, relates to the field of artificial intelligence, and in particular to intelligent transportation. A specific implementation solution includes: acquiring features corresponding to multiple candidate points of interest; determining predicted popularity of the multiple candidate points of interest according to a mapping relation between each feature and each popularity and the features of the multiple candidate points of interest, and the mapping relation is determined based on the frequency of operations performed by a user for each sample point of interest in a historical time period; and displaying the candidate points of interest of which predicted popularity meets a preset popularity condition in a map. Therefore, the accuracy of the displayed points of interest may be enhanced.