51 results about "Spatial code" patented technology

A system and method are provided for identifying a one- or multi-dimensional spatial code comprising a plurality of security tags with one or more characteristic emission profiles. The spatial codes are identified on the basis of the combined spatial and spectral information. The system for identifying such spatial codes is comprised of a beam source, a detector, and a processor. The method includes illuminating the code, recording the light emission at a plurality of wavelengths, decoding the spatial information, resolving the spectral profiles, and identifying the code based on the spatial and spectral information. The system and method are applicable to validating a spatial code.

The invention provides a computer-implemented chunking process (named “OP”) to assign and physically associate unique spatial representations (“chunk codes”) in one representational (coding) space (“chunk coding space”) with unique temporal sequences of spatial codes (“items”) in another coding space (“item coding space”). OP differs from all prior chunking processes in that, for any particular item sequence, it activates a unique chunk code for that sequence during presentation of that sequence's first item, even if other sequences from the input domain may begin with the same item.

The invention discloses a hyperspectral super-resolution computational imaging system based on compression sensing, which comprises a liquid crystal adjustable filter, a spatial coding module, an areaarray detector, a compression reconstruction module and a super-resolution module. After the original image passes through the LCD adjustable filter and the spatial coding module, it is detected by the area array detector to obtain the hyperspectral data which is compressed in space and spectral dimension. The compression reconstruction module is configured to reconstruct the hyperspectral data by using a compression sensing reconstruction algorithm to obtain a restored low-resolution hyperspectral image. A super-resolution module is configured to recover a high-resolution hyperspectral imagefrom only the low-resolution hyperspectral image without supplementing the high-resolution RGB image by utilizing the non-local self-similarity of the hyperspectral image. The super-resolution moduleis configured to recover a high-resolution hyperspectral image from the low-resolution hyperspectral image without supplementing the high-resolution RGB image. At that same time, the system does notneed to add additional optical path to realize the super-resolution reconstruction of the hyperspectral image.

A system and method for encoded microparticles is described. One embodiment includes an encoded microparticle comprising a plurality of segments, wherein the plurality of segments form a spatial code; contrast coating on at least one segment of the plurality of segments, wherein the contrast coating further encodes the microparticle; an outer surface, wherein the outer surface encloses the spatial code and contrast coating, and wherein the spatial code and contrast coating are detectable through the outer surface.

The present application provides a data retrieval method and device based on spatial coding, which relates to the technical field of massive spatial data processing. The data retrieval method based onspatial coding comprises the following steps: acquiring spatial data to be retrieved; the spatial data to be retrieved being converted into a code value to be retrieved by adopting a spatial data coding algorithm; calculating a retrieval row key according to the code value to be retrieved; determining a position of a target code value corresponding to the search row key in a preset non-relationaldatabase; a target code value being read from that preset non-relational database accord to a position of the target code value, and spatial data corresponding to the target code value being obtained. The present application converts the spatial data into a coded value by a spatial coding algorithm, and constructs a spatial index in a non-relational database by using the coded value, thereby effectively improving the retrieval and analysis efficiency of the spatial data.

The invention discloses a cabinet intelligent design method and device based on representation learning, equipment and a medium. The method comprises the steps: acquiring cabinet body information and cabinet body space environment information in historical data; constructing a feature project according to the cabinet body information and the cabinet body space environment information; constructing a coding learning model according to discrete features in the feature project; training the code learning model to obtain a spatial code of a historical cabinet object and a code prediction model; and inputting to-be-arranged space information and standard household plate information into the code prediction model to obtain a target design space code, solving similarity between the code and the spatial code of the historical cabinet object, and determining the cabinet object with the highest similarity as the cabinet object. According to the method, a rapid and reasonable cabinet design scheme meeting diversity is provided for the classification customization design process, the cabinet design efficiency is improved, and the method can be widely applied to the technical field of smart home.

The invention provides a spatial coding structured light three-dimensional scanning method and system. The method comprises the steps: designing a single-frame spatial coding pattern which comprises adecoding point for decoding and an encryption point for encryption; projecting a pre-coded single-frame space coding pattern to the surface of a measured object through a projector; shooting the space coding pattern modulated by the object by a camera, and extracting an image decoding point and an encryption point; determining a candidate projector column number of a decoding point by utilizing ahorizontal epipolar constraint and a neighborhood relative displacement relationship ; constructing and updating a statistical weight array of the decoding point, and deleting and selecting the candidate projector column number of the decoding point according to the statistical weight array; deducing the projector column number of the encryption point according to the projector column number of the decoding point; and reconstructing a point cloud according to the image coordinates of the decoding point and the encryption point and the corresponding projector column number. Therefore, problemsthat a traditional spatial coding structure is low in light robustness, poor in precision, large in decoding requirement for image space, poor in expansibility and the like are solved.

The invention discloses a network traffic matrix prediction method based on a self-attention mechanism, which relates to the technical field of network traffic prediction and comprises the step of scaling network traffic data to a specified range. And constructing a shortest path tree of all nodes in the target network, coding according to all the shortest path trees to obtain a spatial code, and adding the spatial code to the network flow data. And coding the timestamps of the network flow data according to different granularities to obtain time codes, and adding the time codes to the network flow data. And constructing a traffic prediction model based on a self-attention mechanism by using a trainable position code and the network traffic data, and performing traffic prediction. Through utilization of time and space correlation information of network traffic, a self-attention mechanism can fully mine potential features of the traffic, and the accuracy of long-time prediction of a network traffic matrix is improved.

The invention discloses an imaging method and device based on spatial coding, the imaging method is realized through an imaging device, the imaging device comprises a camera, a projector and a processor, the projector is a color laser projector, and the imaging method comprises the following steps: the processor calibrates the camera and the projector; wherein the projector projects a preset image, and the preset image respectively projects sine wave structured light and a spatial coding image through a monochromatic laser in the projector; analyzing the mixed image is analyzed to obtain sine wave structured light data and spatial coding data; the processor obtains the absolute phase shift of the sine wave structured light; wherein the projector projects sine wave structured light on a target object; the camera shoots an object image of the target object projected by the sine wave structured light; and the processor obtains a three-dimensional model of the target object according to the absolute phase shift of the sine wave structured light and the object image. The method has the advantages that the operation speed is high, the time for obtaining the model of the object is short, and the model precision is high.

The invention discloses a model acquisition method and device based on spatial coding. The model acquisition method is realized through a model acquisition device, the model acquisition device comprises a camera, a projector and a processor, and the model acquisition method comprises the steps that the processor calibrates the camera and the projector, the projector projects the sine wave structured light and a spatial coding image, the camera shoots the sine wave structured light to generate a structured light image and shoots a spatial coded image to generate a coded image, the processor obtains the absolute phase shift of the sine wave structured light according to the corresponding relation between the structured light image and the coded image, the projector projects the sine wave structured light on a target object, the camera shoots an object image of the target object projected by the sine wave structured light, and the processor obtains a three-dimensional model of the targetobject according to the absolute phase shift of the sine wave structured light and the object image. The method and the device have the advantages that the operation speed is high, the time for obtaining the model of the object is short, and the model precision is higher.

A method for parametric spatial audio coding of a multi-channel audio signal comprising a plurality of audio channel signals is provided, the method comprising: calculating at least two different spatial coding parameters for an audio channel signal of the plurality of audio channel signals, wherein the at least two different spatial coding parameters are of at least two different types of spatial coding parameters and are calculated with regard to a reference audio signal, wherein the reference audio signal is another audio channel signal of the plurality of audio channel signals or a downmix audio signal derived from at least two audio channel signals of the plurality of audio channel signals; selecting at least one spatial coding parameter of the at least two different spatial coding parameters associated with the audio channel signal on the basis of the values of the calculated spatial coding parameters; including a quantized representation of the selected spatial coding parameter into a parameter section (1b) of an audio bitstream (1); and setting a parameter type flag in the parameter section (1b) of the audio bitstream (1) indicating the type of the selected spatial coding parameter being included into the audio bitstream (1).

This disclosure demonstrates an approach that translates synthetic DNA codes to spatial codes registered in nanoliter microchambers for multiplexed measurement of nearly any type of molecular targets (e.g., miRNAs, mRNAs, intracellular and surface proteins) in single cells.

The invention relates to a spatial-temporal data management method and system, a host and a computer readable storage medium. The method comprises the following steps: acquiring spatial-temporal data; layering the spatial-temporal data, and coding the layered spatial-temporal data according to a spatial coding rule to obtain a primary key; and according to a fragmentation storage rule, dividing the spatial-temporal data according to the primary key, and then storing divided data in to servers in a column database. According to the method, the storage capability and the retrieval efficiency of the spatial-temporal data can be improved.

The invention discloses an industry address serial number generation method and device based on spatial grids. The method comprises the steps of carrying out the coding of map data, obtaining the spatial grids corresponding to the map data, and the spatial grids having spatial grid codes in one-to-one correspondence; calculating spatial grids corresponding to a plurality of longitude and latitudeinformation of the industry address data; obtaining a reference grid code through calculation, and a spatial grid corresponding to the reference grid code being located in the Kth layer of space hierarchy; judging whether the spatial grid code corresponding to the Nth longitude and latitude information is the same as the reference grid code or not, and if so, taking the spatial grid code as an industry address serial number of the industry address data; and if not, updating the grid code corresponding to the K-1th spatial hierarchy into the reference spatial code until industry address serialnumbers corresponding to all longitudes and latitudes in all industry address data are obtained. According to the embodiment of the invention, a large amount of floating point operation is not needed,and the generation efficiency of the industry address sequence number can be effectively improved.

The invention belongs to the field of optics, and discloses a target intelligent sensing and recognition system and method based on space coding, and the system comprises a coding module and an imaging module. The encoding module encodes the target recognition model into a weight value corresponding to each pixel unit in the space, and inputs the weight value into a spatial light modulator in the imaging module; and the imaging module performs spatial coding on the optical signal by using a spatial light modulator, acquires the spatially coded optical signal through a single-channel photoelectric detector, and realizes intelligent identification of a target by using a single-channel measurement value. According to the method, space coding is carried out on the collected optical signals, post-processing of the image is achieved while optical measurement is carried out, the complex image post-processing process is effectively avoided, and the time efficiency of target sensing and recognition is greatly improved. According to the method, the equipment cost caused by image data transmission, storage and the like can be reduced. Therefore, the method has important potential application value in the field of target perception and recognition.