Abstract: A cross-regional travel recommendation method and apparatus, an electronic device and a storage medium are provided, which relates to the fields of intelligent transportation and deep learning. A specific implementation solution is: acquiring a travel request of a user, the travel request comprising a start point and an end point which are located in different regions; extracting user features according to the travel request of the user; and recommending at least one travel plan to the user according to the user features and a pre-trained cross-regional travel recommendation model. The technical solutions can make up for the deficiency of the existing technology, provide a cross-regional travel plan recommendation under a large-space scale and a multimodal environment through a pre-trained cross-regional travel recommendation model and user features extracted based on a travel request of a user, and can satisfy a cross-regional travel request of the user, and is highly practical.

Abstract: A machine translation method includes: obtaining first target language text by performing first translation on source language text using an initial NMT model; identifying an untranslated part in the source language text based on the source language text and the first target language text; obtaining an adjusted NMT model by increasing an attention weight corresponding to the untranslated part in the initial NMT mode; and obtaining second target language text by performing second translation on the source language text using the adjusted NMT model.

Abstract: A method is provided. The method includes: obtaining global position and orientation information of a first trajectory point; determining at least one pair of second trajectory points based on the global position and orientation information; obtaining a relative position and orientation estimation information and a relative position and orientation measurement information of each pair of second trajectory points; and calculating a local rotation offset at the first trajectory point based on the relative position and orientation estimation information and the relative position and orientation measurement information of each pair of second trajectory points in the at least one pair of second trajectory points to correct the global position and orientation information.

Abstract: A semantic classification model training method includes that a sample query template and a label category of at least one category to be predicted in the sample query template are acquired, where the sample query template is constructed according to a sample query statement and a number of the at least one category to be predicted; the sample query template is input to the pre-constructed semantic classification model to obtain a sample semantic category of the at least one category to be predicted; and the semantic classification model is trained according to the sample semantic category and the label category of the at least one category to be predicted.

Abstract: Embodiments of the present application disclose a file directory traversal method, apparatus, device, and medium, and relate to the field of file system processing technology and cloud computing. The method may include: receiving a current directory traversal request of a terminal for a target directory; determining a directory calling identifier of the terminal by parsing the current directory traversal request; wherein, the directory calling identifier is used for uniquely representing the terminal under the target directory; determining a directory entry currently requested to be called by the terminal under the target directory, according to the current directory traversal request; and sending the determined directory entry to the terminal in accordance with the directory calling identifier.

Abstract: An image detection method and apparatus, an electronic device and a storage medium are provided, which relate to the fields of artificial intelligence, deep learning and image processing. The image detection method comprises: performing an acquisition processing on a to-be-detected imaging image to obtain an acquired image; extracting feature data of a target object in the acquired image through a preset image detection network in response to detection processing; performing a multi-dimensional detection comprising at least an imaging content indicator and a color bar indicator on the feature data of the target object according to the image detection network to obtain a detection result; wherein the target object includes imaging contents and color bars which are used to describe color information related to the imaging contents.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for constructing a quality evaluation model, an electronic device and a computer-readable storage medium. A specific implementation mode of the method comprises: acquiring samples of knowledge contents; extracting statistical features, semantic features, and image features respectively from the samples of knowledge contents; and constructing a quality evaluation model for knowledge according to the statistical features, the semantic features, and the image features. On the basis of the prior art, this implementation mode additionally uses semantic features and image features of knowledge contents to construct a more accurate quality evaluation model based on multi-dimensional features that characterize the actual quality of a knowledge, which may well discover some brief but very useful summary knowledge in an enterprise and may recommend high-quality knowledge more accurately for employees in the enterprise.

Abstract: Provided are a green wave speed determination method, an electronic device and a storage medium, which relates to the field of artificial intelligence, particularly, the field of intelligent traffic technology. The implementation scheme is as follows: a stop position of a vehicle to be detected at an intersection and waiting time of an indicator light at the intersection are acquired; and a green wave speed of the vehicle to be detected is determined according to a traffic condition type, the stop position and the waiting time.

Abstract: Provided are a method and apparatus for controlling video playing, an electronic device and a storage medium. The solution is as follows: in response to at least one video being playing or paused on a display screen, acquiring a current face image of a user in front of the display screen; parsing the current face image by using an augmented reality-based gaze tracking method to determine a current visual focus of the user on the display screen; and controlling, according to the current visual focus, the at least one video to continue playing or be paused on the display screen.

Abstract: Embodiments of the present application disclose a positioning method and apparatus, an autonomous driving vehicle, an electronic device and a storage medium, relating to the field of autonomous driving technologies, comprising: collecting first pose information measured by an inertial measurement unit within a preset time period, and collecting second pose information measured by a wheel tachometer within the time period; generating positioning information according to the first pose information, the second pose information and the adjacent frame images; controlling driving of the autonomous driving vehicle according to the positioning information. The positioning information is estimated by combining the first pose information and the second pose information corresponding to the inertial measurement unit and the wheel tachometer respectively. Compared with the camera, the inertial measurement unit and the wheel tachometer are not prone to be interfered by the external environment.

Abstract: The present disclosure provides a route processing method and apparatus. The specific implementation includes: acquiring a vehicle driving route according to a standard definition map, where the vehicle driving route comprises multiple standard definition map road sections of the standard definition map; determining at least one first road section from the multiple standard definition map road sections according to a road section mapping relationship between the standard definition map and a high definition map, where each first road section has a unique corresponding target road section in the high definition map; determining the target road section corresponding to each first road section in the high definition map according to the road section mapping relationship; and determining a target driving route corresponding to the vehicle driving route in the high definition map according to the target road section corresponding to each first road section and the high definition map.

Abstract: A method, apparatus, device and medium for coding a video are provided. An implementation plan includes: determining an initial video frame structure based on a preset threshold for a B-frame number; in response to determining that the initial video frame structure meets a preset condition, shortening the initial video frame structure to obtain a candidate video frame structure set; determining a target video frame structure from the candidate video frame structure set; and performing video coding on video frames in a to-be-coded video frame sequence according to the target video frame structure.

Abstract: Embodiments of the present disclosure provide an image recognition method and apparatus, an electronic device and a medium, and relates to the field of image processing. The method may include: acquiring a to-be-recognized image sent by a client, and determining whether the to-be-recognized image is a back image; determining characteristic information of the to-be-recognized image in at least one dimension, when it is determined that the to-be-recognized image is the back image; and determining a target front side image matching the to-be-recognized image according to the characteristic information, and returning the target front side image to the client to cause the client to display the target front side image.

Abstract: Embodiments of the present disclosure provide a method and apparatus for detecting a target object, an electronic device, and a computer readable storage medium. The method may include: acquiring a to-be-detected image; processing the to-be-detected image using an object detection model including a deformable convolutional layer to obtain an offset prediction result of the deformable convolutional layer; and adjusting a size of an anchor point using the offset prediction result, and determining position information of the target object in the to-be-detected image using the anchor point of the adjusted size.

Abstract: A method for determining a competitive relation of Points of Interest (POI), and a device are provided in the present disclosure. The specific implementation includes: determining POI representation data between two target POIs based on service-related data of the target POIs; and determining a competitive relation between the target POIs based on the POI representation data.

Abstract: Provided are a quantum chip structure, a determining method, a device and a storage medium, and relates to the field of computer technology, and in particular, to the field of quantum computation. The quantum chip structure includes: a ring structure composed of n center qubits, where two adjacent center qubits in the ring structure are connected through a coupler; and n is a natural number greater than or equal to 3; and two-linear structures drawn from a center qubit Qi toward outside of the ring structure; where a first linear structure in the two-linear structures contains ai first qubits; and a second linear structure in the two-linear structures contains bi second qubits. In this way, a quantum chip structure with high connectivity is obtained.

Abstract: Exemplary embodiments of the present disclosure provide a method and apparatus for determining road information data and a computer storage medium, which may be used for autonomous driving, road information prediction, and driving route planning. The method for determining road information data includes: determining, via a precision navigation device of a vehicle, a plurality of locations of the vehicle; acquiring, via a sensor of the vehicle, a plurality of image frames of a physical environment where the vehicle is located; determining, from the plurality of locations, a target location corresponding to at least one image frame among the plurality of image frames; and determining, based on the determined target location and a map related to the physical environment, road information data corresponding to the at least one image frame. According to the solution of the present disclosure, road information annotation data may be accurately and efficiently generated.

Abstract: Provided are a method and apparatus for determining image depth information, an electronic device, and a medium. The method includes: acquiring first depth information of pixels in a target image output by a first prediction layer; generating the point cloud model of the target image according to the first depth information, and determining initial depth information of the pixels in the target image in a second prediction layer according to the point cloud model; and performing propagation optimization according to the initial depth information, and determining second depth information of the pixels in the target image output by the second prediction layer, where the first prediction layer is configured before the second prediction layer.

Abstract: A method, apparatus, device and readable medium for transfer learning in machine learning are provided. The method includes: constructing a target model according to the number of classes to be achieved by a target task and a duly-trained source model; obtaining a value of a regularized loss function of the corresponding target model and a value of a cross-entropy loss function of the target model, based on sets of training data in a training dataset of the target task; according to the value of the regularized loss function and the value of the cross-entropy loss function corresponding to each set of training data, updating parameters in the target model by a gradient descent method to implement the training of the target model. The above technical solution avoids excessive constraints on parameters in the prior art, thereby refraining from damaging the training effect of the source model on the target task.

Abstract: A refrigeration system is provided. The refrigeration system includes: an indoor heat exchange module configured for refrigerant to absorb heat; outdoor heat exchange modules for the refrigerant to dissipate heat. The outdoor heat exchange module includes a compression device and a condensing device; the outdoor heat exchange module is switchable between an active mode and a standby mode; in the active mode, the outdoor heat exchange module is connected to the indoor heat exchange module; in the standby mode, the outdoor heat exchange module is disconnected from the indoor heat exchange module, and the compression device of the outdoor heat exchange module is in an operation status.