424 results about "Direction information" patented technology

Provided are an apparatus and method for operation of an apparatus in a wireless communication system. The apparatus may be a UE, a chipset, or a base station. The UE receives an FD configuration message notifying a full duplex symbol from among a plurality of symbols, receives a cell-specific common TDD configuration message, and receives a UE-specific dedicated TDD configuration message. Here, only for the full duplex symbol from among the plurality of symbols, second direction information notified by the dedicated TDD configuration message overrides first direction information notified by the common TDD configuration message.

The invention belongs to the technical field of remote sensing image processing, particularly relates to an urban remote sensing image segmentation method and system based on bidirectional coordinate attention and multi-scale adaptive feature fusion, and provides a remote sensing image semantic segmentation neural network architecture taking an attention re-calibration module as a decoder core. Wherein the encoder path gradually extracts multi-scale feature representation through cascaded residual convolution blocks and down-sampling operation to form a feature pyramid of which the spatial resolution is reduced step by step and semantic information is enhanced step by step; the decoder path gradually recovers the spatial resolution through cascaded up-sampling and feature refining operations to generate a precise segmentation mask; a space-channel dual attention re-calibration module oriented to a decoding stage is provided, through explicit coding of space coordinate direction information and combination of global channel dependence modeling, features beneficial to semantic discrimination are adaptively enhanced in the feature fusion and resolution recovery process, and therefore segmentation precision and consistency are improved.

An image processing apparatus is disclosed. The image processing apparatus includes a communicator configured to transmit or receive information to or from an intraoral scanner, a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory to identify an oral image obtainment mode based on tip information about a tip included in the intraoral scanner, and obtain an oral image based on two-dimensional image data received from the intraoral scanner through the communicator and the identified oral image obtainment mode, wherein the tip information may include at least one of tip fastening direction information and tip size information.

The invention discloses an extractor hood and a control method and a control device thereof.The extractor hood comprises at least two independently-lifting smoke gathering cavities, and the control method comprises the steps that a neural network model is adopted, and based on first video information, first image information and oil smoke concentration information of a target cooking area, the first video information and the first image information are obtained; determining cookware size information, cookware type information, cooking temperature information, concentration standard exceeding information and cooking fume movement information; the lampblack movement information comprises lampblack speed information and lampblack direction information; according to the pot type information, the cooking temperature information, the concentration standard exceeding information and the oil smoke speed information, the suction demand level of the target cooking area is determined; according to the suction demand level and the cookware size information, the target height of a smoke gathering cavity corresponding to the target cooking area is determined, and the smoke gathering cavity is controlled to descend to the target height from the initial position. According to the technical scheme, the oil smoke suction efficiency of the range hood in a complex cooking scene can be improved, and the use experience of a user is improved.

The invention discloses a daily load curve clustering method based on a mixed distance improved FCM algorithm, and belongs to the technical field of data processing, and the method comprises the steps: collecting daily load data of a user at a sampling frequency of 5 minutes, carrying out the corresponding data preprocessing, analyzing the fluctuation characteristics of a daily load curve, and carrying out the clustering of the daily load curve; euclidean distance representing load curve power amplitude information and cosine distance representing load curve power fluctuation direction information are constructed respectively, and then an entropy weight method is adopted to construct a hybrid similarity distance (HSD) fusing the Euclidean distance and the cosine distance as a similarity criterion between daily power load curves; replacing the Euclidean distance in the FCM algorithm with the constructed HSD, then calculating a corresponding membership degree and a clustering center, iteratively updating the membership degree and the clustering center by using a target function based on an intra-class error weighted quadratic sum, and completing daily load curve clustering according to a preset maximum iteration number; and finally, determining the optimal clustering number and the corresponding optimal daily power load curve clustering result by using the sum of intra-class errors (SAE), thereby effectively solving the prominent problems of poor effect, low efficiency and the like of the traditional power load curve clustering method.

The embodiment of the invention provides a method executed by electronic equipment, the electronic equipment and a storage medium, and relates to the field of artificial intelligence. The method comprises the following steps: acquiring an input first audio signal; based on direction of arrival (DOA) information of a first audio signal, target direction information and spatial information of a physical microphone (RM) of the electronic equipment, obtaining the number and positions of virtual microphones (VM); a second audio signal is obtained based on the first audio signal and the number and location of VMs. Optionally, the method performed by the electronic device may be performed using an artificial intelligence model.

The invention discloses an ultrasonic guided wave damage ellipse imaging positioning method and equipment for a layer decreasing composite material laminated plate. The method comprises the following steps: S1, acquiring thickness change direction information of the laminated plate and position coordinates of an excitation transducer and a receiving transducer; s2, according to the material characteristic parameters, simulating and calculating the propagation time of ultrasonic guided waves transmitted from an excitation transducer to any point to generate a first theoretical propagation time map, and simulating and calculating the propagation time of the ultrasonic guided waves transmitted from any point to a receiving transducer to generate a second theoretical propagation time map to generate a second theoretical propagation time map; coupling influence of thickness change and material anisotropy on guided wave propagation is considered in the simulation process; s3, transmitting an ultrasonic guided wave signal, and extracting the actual flight time of a damaged wave packet; s4, calculating theoretical total propagation time, and determining a candidate area where damage exists; and S5, on the basis of repeated operation of the multiple groups of transducer pairs, taking a plurality of candidate region intersections to determine a final damage position. The objective of the invention is to solve the positioning error problem caused by the structural characteristics of a laminated plate in a traditional algorithm, and to realize more accurate damage detection and positioning.

The invention relates to the technical field of space telescope calibration, in particular to a telescope pointing calibration method based on optical fiber interconnection, which comprises the following steps: providing reference light beams in different directions, enabling each lens to correspondingly receive the reference light beams by adjusting the lens pointing, splitting the reference light beams received by the lenses through an optical splitter, and obtaining a split beam; one beam is aligned and corrected through a camera, and the other beam is coupled into an optical fiber to record direction information; the calibration light beams are reversely emitted by the optical fiber through the optical switch and are emitted by the lens, each reference light beam in the known direction is reproduced, a reference light field is formed, the telescope to be calibrated is placed in the reference light field, the miss distance of each calibration light beam in the known direction on the mirror surface of the telescope to be calibrated is measured, and the pointing error is calculated and corrected according to the miss distance. The optical fiber network is used for establishing the unique mapping relation between the space direction and the optical fiber channel, miss distance measurement is carried out through dynamic time-sharing reproduction, and the problems of mechanical accumulative errors and the like existing in a traditional mechanical calibration method are solved.

The invention discloses an intelligent parking system and a vehicle parking management method, and relates to the technical field of intelligent traffic and Internet of Things, and the method comprises the steps: S1, collecting vehicle position signals and vehicle image features, and carrying out the data fusion, and obtaining the real-time coordinates of a vehicle with direction information; s2, constructing a continuous track chain based on the real-time coordinates of the vehicle, and recognizing abnormal behaviors of the vehicle based on a preset track feature threshold value; and S3, generating and executing a corresponding barrier gate control instruction according to the abnormal behavior of the vehicle. According to the method, geomagnetism and video sensing data are fused in a dynamic self-adaptive mode, a vehicle continuous track chain is constructed, abnormal behaviors such as vehicle retention and turning around can be accurately recognized, real-time linkage with barrier gate control is achieved, and therefore the vehicle smashing prevention safety, the accuracy of illegal behavior recognition and the real-time performance of system response are effectively improved.

The invention discloses a two-stage multi-modal 3D target detection method based on space-semantic-range multi-dimensional joint modeling, and the method comprises the steps: collecting the multi-modal data of a 3D target, fusing an RGB image and a LiDAR point cloud through an image-guided depth completion technology, and generating a virtual point cloud; frame labeling is carried out on the 3D target in the partial virtual point cloud to obtain full-labeling data, and the full-labeling data comprises a 3D bounding box surrounding the 3D target, a category label and direction information; constructing a dual-stage multi-modal 3D target detection model of dual-stage multi-dimensional joint modeling, wherein the model comprises a spatial perception sampling sub-module, a multi-dimensional importance score sampling sub-module, a sparse convolutional backbone network, a distance perception sub-network and a detection head; the full-annotation data and the virtual point cloud serve as training data, a two-stage multi-mode 3D target detection model is trained, then a 3D bounding box, a category label and direction information in the full-annotation data serve as true values, a loss function is calculated, detection head parameters are trained, and the trained model is the 3D target detection model; and inputting a virtual point cloud generated by performing depth completion on the RGB image and the LiDAR point cloud into the trained 3D target detection model to obtain a 3D bounding box, category information and direction information of the 3D target.

A method performed by an apparatus of a vehicle, the method includes: generating one or more image features from one or more images using an image analysis model; producing a reference BEV feature with reference direction information at a reference level and a height BEV feature with height direction information for each level by mapping the image features to a BEV grid; calculating a weight based on information in the reference BEV feature and the height BEV feature; and generating a single enhanced BEV feature by applying the calculated weight to the reference BEV feature and the height BEV feature.

The invention relates to the technical field of image recognition, in particular to a printed circuit board defect detection method and system based on image recognition. The method comprises the following steps: collecting a multi-angle board image of a printed circuit board to be detected, and determining a highlight saturation region according to gray gradient information in the multi-angle board image; weighting and correcting the pixel value of the highlight saturation region by using the pixel brightness information of the neighborhood of the highlight saturation region, and generating an image to be analyzed; identifying silk-screen character information in the to-be-analyzed image, and generating a character bounding box according to the silk-screen character information; combining the gray distribution information and the edge direction information in each character bounding box to reconstruct a character coverage texture, and generating a to-be-detected image; and according to a preset circuit board defect library, matching defect features in the to-be-detected image, and generating a defect detection report according to a matching result. According to the invention, the detection efficiency is obviously improved, and the method is suitable for the production detection requirements of high-density and high-precision PCBs.

The embodiments of the present disclosure provide a method performed by an electronic apparatus, the electronic apparatus, and a storage medium, which involves the field of artificial intelligence. The method includes: obtaining an input first audio signal; obtaining a number and positions of virtual microphones (VMs) based on direction of arrival (DOA) information of the first audio signal, target direction information and spatial information of real microphones (RMs) of the electronic apparatus; and obtaining a second audio signal based on the first audio signal and the number and positions of the VMs. Alternatively, the above method executed by electronic apparatus may be executed by using artificial intelligence models.

The application discloses a cloud application interface processing system, method, device and equipment. The system sends interface content information and interface format information of a cloud application to a terminal device through a first cloud application processing module deployed on a server, and presents the interface content information on a display unit according to the interface format information and display direction information of the terminal device through a second cloud application processing module deployed on the terminal device. In this way, the device can adjust the display of the cloud application interface that is accidentally rotated according to the interface format information, and the problem of inverted display of interface content can be solved without relying on third-party application adaptation, so that a mobile phone application can be directly transplanted into a cloud application scene for use. Therefore, the use experience of a cloud application user can be effectively improved, the expansion scene of the cloud application can be improved, and the development workload of a third-party application can be reduced.

The invention relates to the field of gamepads, and discloses a gamepad convenient for multi-mode switching and a gamepad control method.The gamepad comprises an operation recording unit, an operation analysis unit and a mode switching unit, the operation recording unit is used for recording operation records of a user on keys of the gamepad, and the operation analysis unit is used for analyzing the operation records of the user on the keys of the gamepad; the operation analysis unit is used for analyzing operation records of a user on keys of the gamepad and determining mode switching information, and the mode switching unit is used for switching control modes of the gamepad according to the mode switching information; wherein the operation record of the user on the keys of the gamepad comprises key information, rocker swing amplitude information and rocker swing direction information, and the mode switching information is used for controlling the gamepad to be switched among a plurality of preset control modes. The control modes such as the rocker force of the gamepad can be automatically controlled, and the using effect of the gamepad is improved.

The invention relates to the field of camera calibration, in particular to a calibration method, device and equipment for a yaw angle of a vehicle foresight camera and a medium. The method comprises the following steps: acquiring a driving direction information sequence of a vehicle in a straight driving state; according to the driving direction information sequence, obtaining a reference driving direction of the vehicle driving along a straight line; determining the actual driving direction of the vehicle at the target moment based on the driving direction information at the target moment in the driving direction information sequence; determining a compensation yaw angle according to the deviation between the actual driving direction and the reference driving direction; and on the basis of the compensation yaw angle, calibrating an estimated value of the external parameter yaw angle of the foresight camera at the target moment, and obtaining a calibration value of the external parameter yaw angle of the foresight camera.

It stably controls the movement of a moving object based on the movement of the object it is following. [Solution] Information indicating the position and direction of movement of a person is acquired. A graph consisting of nodes and edges, showing the person's movement path, is acquired. Based on the person's position, a first edge of the graph corresponding to the person's position is determined. Based on the first edge or one or more edges located in the direction of the person's movement relative to the first edge, the target position of the moving object is determined.

A system is disclosed. The system may include a receiver or transmitter node. The receiver or transmitter node may include a communications interface with an antenna element. A controller may include one or more processors and have information of own node velocity and own node orientation relative to a common reference frame. The receiver or transmitter node may be time synchronized to apply Doppler corrections to signals, the Doppler corrections associated with the receiver or transmitter node's own motions relative to the common reference frame, the Doppler corrections applied using Doppler null steering along Null directions. The system may be configured to, via the Doppler null steering, flood a communication data packet to a destination node based on a spatial awareness. The system may limit the flooding to only be towards the destination node and / or for a maximum number of hops.

This application provides a method, system, two-wheeled vehicle, and group for extrinsic parameter calibration of a two-wheeled vehicle camera network, relating to the fields of photogrammetry and calibration. The method includes: receiving marker point position and direction of travel information packets and acquiring real-shot images; extracting real-shot versions of marker points from other two-wheeled vehicles from the real-shot images; parsing the marker point position and direction of travel information packets to obtain a list of neighboring two-wheeled vehicle marker points corresponding to the real-shot images; calculating the coordinates of each projected marker point in the vehicle's coordinate system with the vehicle's camera as the origin; estimating the coordinates of the projected marker points in the pixel coordinate system; and, under conditions that meet automatic calibration requirements, determining the correspondence between the real-shot marker points and the projected marker points, and calibrating the extrinsic parameters of the vehicle's camera based on this correspondence. This method reduces dependence on external calibration objects, enabling real-time calibration in dynamic environments and improving the efficiency of automatic calibration of camera extrinsic parameters.

The present invention provides a navigation control device, a navigation control system, a navigation control method, and a computer program for controlling the navigation of an underwater vehicle toward an area where an aerial vehicle is thought to be flying. [Solution] The navigation control device 10 detects the arrival of sound waves from an object 60 suspended in the water from the flying body 50, inputs direction information indicating the direction of the sound wave's arrival and distance information indicating the distance between the underwater navigating body 30 on which the device is mounted and the object 60, and uses the direction information and distance information to control the navigation of the underwater navigating body 30 toward a target position set below the flying body 50.

The application discloses a parking space detection method and device, electronic equipment and storage medium, and relates to the field of intelligent parking. The method comprises the following steps: performing feature extraction on a target feature image of a to-be-detected parking space image; performing parking space entrance information extraction based on the target feature image to obtain target parking space entrance information; the target parking space entrance information comprises a parking space entrance key point heat map, a parking space entrance center point heat map, parking space entrance direction information and position offset information; determining a target parking space entrance key point corresponding to each parking space entrance according to the parking space entrance key point heat map, the parking space entrance center point heat map and the position offset information; and determining a target parking space based on the target parking space entrance key point and the corresponding direction information. The application determines and corrects the parking space entrance key point by using the parking space entrance center point and the position offset information, and adds the parking space entrance direction information, so that the parking space detection result is more accurate.

An apparatus of a radio unit (RU) may include a radio frequency (RF) switch selectively connected to an uplink path or a downlink path for time division duplex (TDD); at least one processor; and a memory including instructions. When executed individually or collectively by the at least one processor, the instructions may cause the apparatus to: receive a control plane message from a distributed unit (DU) within a downlink receive window; obtaining a segment for downlink scheduling based on data direction information and a segment type indicator of a generic header of the control plane message; and changing a path to which the RF switch is connected from an uplink path to a downlink path on the basis of the segmented command for increasing the symbol number and information for indicating the number of symbols.

The application provides a kind of based on remote sensing image's directed lane center line generation method and system, method includes: the remote sensing image data is input into trained directed lane center line segmentation model, obtains the position prediction image and direction prediction image of lane center line;Line segment detection method is used to obtain line segment information from the position prediction image, the actual geographic coordinates corresponding to line segment are obtained using the coordinate information of remote sensing image data;The RGB data in the same place of the direction prediction image with the coordinate position of the line segment is extracted, and the coordinate difference (dx, dy) between the end and the beginning of the line segment is calculated according to the RGB data;According to the coordinate difference (dx, dy), the direction information of the current line segment is calculated;Iterate position prediction image and direction prediction image, according to the coordinate information and direction information of each line segment, adjust the head-tail connection relationship of each line segment, and obtain directed lane center line data.The application reduces the production cost of lane center line data.

The invention discloses a flight trajectory prediction method and system based on airspace information perception, and the method comprises the steps: obtaining historical aircraft trajectory information, and carrying out the multi-scale flight trajectory segmentation based on downsampling; carrying out aircraft flight mode correlation graph calculation on the aircraft trajectory information of different scales; performing high-order tensor graph neural network construction based on the flight mode correlation graph, and fusing trajectory information of different airplanes in the same airspace; acquiring historical wind speed and wind direction information, and fusing the wind speed and wind direction information with the aircraft trajectory information; and fusing the fusion results according to different scales, and outputting a predicted future aircraft trajectory. According to the method, sufficient information interaction of different airplanes in the same airspace can be ensured, and meanwhile, extra peripheral wind speed and direction information is fused as auxiliary features, so that the flight path is accurately predicted.

The invention discloses a hospital signboard automatic verification method based on image recognition. The method comprises the following steps: obtaining standardized hospital signboard image data; outputting a semantic segmentation mask and a layout structure layout relation matrix; generating a row block sequence index according to the layout structure layout relation matrix, and cutting by using the row block sequence index to obtain a text region sub-image; outputting the structured text information and the corresponding identification confidence information; outputting icon category information, arrow direction information and corresponding confidence information; constructing a normalized cross-modal weight matrix based on the semantic segmentation mask, the layout structure layout relation matrix, the structured text information, the icon category information and the arrow direction information; and generating a verification result, conflict positioning information and a verification confidence score. According to the method, segmentation errors under the conditions of strong light reflection, local shielding and special-shaped typesetting are effectively reduced, and the segmentation accuracy of the small icon and the bent character area is improved.

The invention discloses a hearing aid speech enhancement method and device based on artificial intelligence, and a medium, and relates to the technical field of speech signal processing, and the method comprises the steps: inputting a standardized speech enhancement input feature into a direction perception high-frequency speech enhancement model, extracting a coding feature through a shared coding part in the direction perception high-frequency speech enhancement model, and carrying out the recognition of the coding feature; determining a target sound source direction through a direction information generation part in a direction perception high-frequency speech enhancement model, converting the target sound source direction into direction-related information, and combining the direction-related information with the encoding features to generate direction enhancement features; and inputting the direction enhancement feature into a high-frequency recovery part of a direction perception high-frequency speech enhancement model, performing enhancement processing on a high-frequency band corresponding to the target sound source to obtain high-frequency enhancement data, and compensating the high-frequency enhancement data according to the audiogram of the wearer to obtain individualized high-frequency enhancement frequency domain amplitude data. According to the invention, the recognition capability of the wearer on the target voice is improved.

Embodiments of the present disclosure relate to a line-of-sight estimation method, device, equipment and medium, wherein the method comprises: obtaining a first eye image to be estimated for a line-of-sight direction, and a plurality of second eye images carrying line-of-sight direction information; combining the first eye image and each of the plurality of second eye images to obtain a plurality of image groups; obtaining correlation information between the plurality of image groups, and based on the correlation information between the plurality of image groups, obtaining line-of-sight difference information and weight information corresponding to each of the plurality of image groups; and based on the line-of-sight difference information and the weight information corresponding to each of the plurality of image groups, and the line-of-sight direction information carried by each of the plurality of second eye images, determining a target line-of-sight direction of the first eye image. Embodiments of the present disclosure can additionally determine the correlation information between the plurality of image groups, and determine the line-of-sight direction of the first eye image based on the correlation information, thereby effectively guaranteeing the accuracy and reliability of the final line-of-sight direction.

This invention proposes an automated measurement and verification method for multi-source wave parameters based on neural networks. This method can quantitatively calculate and acquire wave elements, improving the accuracy of wave element measurement. The invention extracts video images frame by frame from nearshore monitoring videos, extracts the features of the buoy based on its motion state on the sea surface, and quantitatively calculates and acquires wave elements, mainly including effective wave period, effective wave height, and wave direction. Simultaneously, it acquires effective wave period, effective wave height, and wave direction information through the wave sensor built into the float, and calculates the wave direction using the float's Beidou module and anchor position. By comparing and verifying in-situ measurements from the float with non-contact measurements from a camera, the methods complement each other, improving the accuracy of wave element measurement.

The invention discloses an imaging parameter correction method capable of automatic focusing and astigmatism correction based on deep learning. The imaging parameter correction method comprises the following steps: acquiring an image as a reference image under a current imaging parameter set; positive increment and negative increment are applied to one or more imaging parameters in the current imaging parameter set to obtain a positive disturbance parameter set and a negative disturbance parameter set, and images are collected under the positive disturbance parameter set and the negative disturbance parameter set respectively to serve as a positive disturbance image and a negative disturbance image; respectively calculating difference images between the positive disturbance image and the reference image and between the negative disturbance image and the reference image; obtaining a prediction parameter adjustment amount by using an imaging parameter correction model based on the difference image; and adjusting the current imaging parameter set according to the predicted parameter adjustment amount. The difference image between the positive disturbance image and the reference image and the difference image between the negative disturbance image and the reference image are provided for the model to carry out adjustment amount prediction, so that the adjustment direction information of imaging parameters is effectively extracted, and the robustness under the condition of a low signal-to-noise ratio is enhanced.

The present invention relates to a haptic information providing system for providing various tactile signals that provide more precise and realistic feedback as if a user is directly touching a physical object in various environments. To this end, the haptic information providing system for providing various tactile signals of the present invention comprises: a directional sensor for detecting a touch position and direction of a user; a multi-channel haptic actuator for providing fine pressure information to the touch position of the user; a multi-channel Peltier element for providing temperature information to the touch position of the user; a multi-channel vibration motor for providing directional information to the touch position of the user; and a controller that detects the touch position on the basis of a directional sensor detection signal and analyzes virtual space input data to control the operations of the multi-channel haptic actuator, the multi-channel Peltier element, and the multi-channel vibration motor.