2164 results about "Decodes" patented technology

The present invention belongs to the technical field of decoding algorithms, and specifically relates to normalized minimum sum decoding of BCH codes and post-processing decoding methods thereof, the steps of which include optimizing the standard form of the check matrix of the BCH code to obtain the best check matrix; inputting the received sequence into the improved normalized minimum sum decoding algorithm NMS based on the best check matrix for decoding; if the decoding is successful, outputting the best decoding estimate; if the decoding fails, inputting the sequence iteration trajectory after the NMS decoding failure into the DIA neural network model, analyzing and outputting the reliability metric of each bit, and then decoding again through the ordered statistical decoder OSD to obtain the best decoding estimate. The present invention successfully achieves the low density of the check matrix, the reduction of the number of short loops, and the uniform distribution of column weights through an innovative check matrix optimization algorithm, and provides a more efficient and better performance BCH code decoding solution.

The invention discloses a camouflage target detection method and system based on cross-scale global and local feature combination, and the method comprises the steps: extracting feature maps of M scales from an input image # imgabs0 # through an encoder, inputting a multi-branch convolution block to obtain enhanced features, inputting the enhanced features into a pre-trained decoder, and carrying out the multi-scale fusion to obtain final fusion features, a decoding result obtained through up-sampling is classified to obtain a camouflage target detection result; wherein the decoder is provided with a # imgabs1 # layer, any # imgabs2 # layer comprises # imgabs3 # decoder nodes, all the decoder nodes are subjected to up-sampling layer by layer and step by step, fusion is carried out through double convolution operation, and then the output features of the decoder nodes are obtained through multi-stage combined scanning feature fusion blocks. The invention aims to solve the detection difficulty when the camouflage target is highly similar to the background, the edge is not obvious or a large amount of shielding exists under the complex background, and overcome the problem that the camouflage target detection precision is low due to the fuzzy edge and the small target size.

An image encoding / decoding method and device according to the present disclosure can induce an intra-prediction mode of the current block on the basis of an induction mode, determine a reference sample of the current block, and generate a prediction sample of the current block on the basis of the intra-prediction mode and the reference sample.

This application discloses a lossless encoding method and apparatus, a lossless decoding method and apparatus, and a device, pertaining to the field of encoding and decoding technologies. The lossless decoding method in embodiments of this application includes: traversing, by an encoder side, a target mesh and obtaining geometry coordinates of each vertex in the target mesh; determining, by the encoder side, vertices with same geometry coordinates as duplicate vertices; merging, by the encoder side, the duplicate vertices in the target mesh to obtain a first mesh; and performing, by the encoder side, lossless encoding on the first mesh to generate a target bitstream.

Disclosed herein is a video decoding method including: obtaining a transform skip mode flag indicating whether transform / inverse transform is skipped in a current block; when transform / inverse transform is skipped in the current block according to the transform skip mode flag, determining that secondary transform / inverse transform is skipped in the current block; and when transform / inverse transform is not skipped in the current block according to the transform skip mode flag, obtaining a transform matrix index for secondary transform / inverse transform of the current block and, determining whether secondary transform / inverse transform is skipped in the current block based on the transform matrix index.

The invention relates to the technical field of artificial intelligence, and discloses a large language model high concurrency reasoning method and system, and the method comprises the steps: calculating the size of a video memory block through an actuator, and distributing a video memory space; the scheduler is used for converting the request sequence and putting the request sequence into a waiting queue of the scheduler; the scheduler allocates a corresponding video memory block to each request sequence until each request sequence can perform next reasoning; the scheduler calculates the video memory requirement of the request sequence in the waiting queue according to the priority sequence, and transfers the request sequence in the waiting queue to the running queue; according to the number of pre-filling types and the number of decoding types of the request sequence, distributing the number of video memory blocks used for executing pre-filling reasoning or decoding reasoning; therefore, according to the method, continuous batch processing, a dynamic space allocation mechanism and a task scheduling framework are adopted, the parallel reasoning capability of continuous batch processing is fully utilized, the concurrency and throughput of large model reasoning are improved, and the limitation that traditional continuous batch processing needs space pre-allocation is solved.

The invention provides a satellite image and actually measured RSRP fused ground radio map generation system, and the system comprises a satellite image feature extraction module which is used for converting a high-resolution satellite image of a target region into high-dimensional image features reflecting the ground feature type distribution of the region; the base station physical characteristic input module is used for converting the physical parameters of the communication base station in the target area into characteristic vectors reflecting electromagnetic propagation characteristics; the multi-modal fusion module is used for fusing the high-dimensional image features and the feature vectors to generate joint feature representation; the radio map decoder is used for generating a radio signal power plane distribution diagram of the target area through a decoding network based on the joint feature representation; and the ground RSRP correction module is used for correcting the radio signal power plane distribution diagram output by the radio map decoder so as to output a final radio signal power distribution result. According to the invention, the space-ground collaborative data source fusion is realized to improve the mapping precision.

The invention provides a lightweight wavelet convolution guide wire segmentation network model and a double guide wire generation method, and the construction of the model comprises the steps: obtaining an input image, carrying out the feature extraction of the input image through a Stem module, obtaining a bottom-layer feature, carrying out the processing of the bottom-layer feature through five wavelet encoders in an iteration manner, and carrying out the recognition of the processed bottom-layer feature through the five wavelet encoders. And inputting the features output by the wavelet encoders into a decoder in an iteration form to carry out decoding processing so as to obtain a segmented prediction map. The method comprises the following steps of: inputting the features output by the wavelet encoders into the decoder in an iteration form to carry out decoding processing on the features output by the wavelet encoders; the wavelet transform attention convolution provided by the invention is specially used for capturing complex edge and texture nuisance features of the guide wire. A channel attention mechanism is introduced after a wavelet decomposition process to enhance feature representation. The combination of channel attention can selectively emphasize key frequency components, significantly improve the ability of the network to capture complex texture modes, and improve the precision of guide wire segmentation.

The invention discloses a multi-stage Mama point cloud completion method and device based on semantic and geometric guidance, and relates to the field of point cloud processing, and the method comprises the steps: constructing and training a multi-stage Mama point cloud completion model based on semantic and geometric guidance, and obtaining a trained multi-stage Mama point cloud completion model; the multi-sorting strategy Mama decoder unit comprises a plurality of stages of multi-sorting strategy Mama decoders which are connected in sequence; obtaining an incomplete point cloud to be complemented and inputting the incomplete point cloud to the trained multi-stage Mama point cloud complementation model, enabling the incomplete point cloud to pass through a Transform-Mama combined point cloud local feature coding unit to obtain coding features, and inputting the coding features into a sparse point cloud generation unit to obtain sparse point cloud; the sparse point clouds are input into the multi-sorting strategy Mama decoder unit to obtain decoding features, the decoding features pass through the point cloud up-sampling unit to obtain predicted complete point clouds, and the problems of quadratic complexity and local detail loss of an existing Transform encoder-decoder structure are solved.

The embodiment of the invention discloses an intelligent downhole operation state monitoring system and method, and relates to the technical field of monitoring data processing. The method comprises the following steps: acquiring multi-modal monitoring data for reflecting an underground operation state; performing fluctuation analysis on each piece of time sequence data in the multi-modal monitoring data to obtain a corresponding fluctuation analysis result; the correlation degree between the fluctuation analysis results corresponding to the different time series data is calculated based on a grey correlation analysis method, and fluctuation correlation information is obtained; performing information fusion on the fluctuation analysis result and corresponding time sequence data through a time window alignment mode to obtain target monitoring data; taking the fluctuation associated information as a weight parameter of an attention mechanism, performing multi-modal feature coding on the target monitoring data through a coding network, and outputting a corresponding operation state representation vector; and inputting the operation state representation vector into a decoding network to carry out downhole operation state anomaly analysis to obtain intelligent downhole operation state monitoring data.

The invention provides a coding method, a decoding method and related equipment. The method comprises the following steps: acquiring a first HDR image and first base layer data corresponding to the first HDR image; determining first intermediate enhancement layer data according to the first HDR image and the first basic layer data; processing the first intermediate enhancement layer data according to a first mapping relation to obtain first enhancement layer data; and encoding the first basic layer data, the first enhancement layer data and the first metadata to obtain a code stream. The first enhancement layer data coded by the technical scheme is determined based on the first mapping relation. Through the first mapping relation, the to-be-coded data can be flexibly processed, so that the coding efficiency can be improved.

A system and method for handling acknowledgments in a wireless system. In some embodiments, the method includes, receiving, by a User Equipment (UE), one or more first transmissions; decoding, by the UE, the first transmissions, to generate a first sub-codebook including one or more corresponding Hybrid Automatic Repeat Request Acknowledgement (HARQ ACK) bit strings each having a first length; receiving, by the UE, one or more second transmissions; decoding, by the UE, the second transmissions, to generate a second sub-codebook including one or more corresponding HARQ ACK bit strings each having a second length, greater than the first length; receiving, by the UE, one or more third transmissions; and decoding, by the UE, the third transmissions, to generate a third sub-codebook including one or more corresponding HARQ ACK bit strings each having a third length, greater than the second length.

The invention provides a physical layer secure antenna selection method based on an MIMO-NOMA system, and relates to the technical field of information security. According to the method, a downlink MIMO-NOMA communication system is established, two kinds of safety antenna selection strategies are designed, the received signal power of legal users is maximized, and the signal power of eavesdropping user receivers is minimized; and the unmanned aerial vehicle transmits the superposed signal, the user receives the signal and decodes the received signal, then the traversal rate of the legal user is solved, and the probability of successfully decoding the transmission information is reduced for the potential eavesdropping user. According to the method, the antenna selection strategy is optimized, the received signal power between the source node and the legal user is maximized, the probability that the eavesdropping user successfully decodes the legal signal is reduced, and the secrecy performance of the system can be improved while the service quality of the legal user is ensured.

A video dynamic mesh coding (v-DMC) decoding system, includes a de-multiplexer that receives and demultiplexes an encoded v-DMC bitstream into: a parameter set and mesh data, geometry, atlas data, and attribute video substreams. The decoding system also includes: a mesh data substream decoder; a video decoder that decodes the geometry data substream; an atlas data substream decoder; a mesh subdivision component that subdivides the one or more base meshes into one or more resampled base meshes based upon the decoded atlas data; a displacement decoder that outputs one or more displacements to verticies of the one or more resampled base meshes; a mesh position refinement component that applies the one or more displacements to the one or more resampled base meshes and outputs one or more resultant meshes; and a video decoder that decodes the attribute video substream into one or more texture images.

The invention discloses a multidisciplinary coupling surface extensible communication data coding method, decoding method, device and equipment, and relates to the field of multidisciplinary coupling numerical simulation, and the method comprises the steps: coding a plurality of to-be-communicated coupling data values of any physical quantity type and type of a plurality of coupling interfaces and coupling data basic information into a coupling data array, data communication on a plurality of coupling interfaces can be completed through one-time calling of the message passing interface, the calling frequency of the message passing interface is greatly reduced, coupling data communication can be carried out on physical data in subject solvers of different numerical simulation methods according to the same encoding and decoding format, coupling data types can be randomly expanded, and the coupling data communication efficiency is improved. The development difficulty of multidisciplinary coupling analysis software is reduced, and the efficiency of multidisciplinary coupling analysis is improved.

The embodiment of the invention provides a decoding method, and the method comprises the steps: decoding a code stream at a decoding end, and determining a prediction mode parameter; when the prediction mode parameter indicates that the intra-frame prediction value is determined by using the MIP, decoding the code stream, and determining the MIP parameter of the current block; decoding the code stream, and determining a transformation coefficient and an LFNST index sequence number of the current block; when the LFNST index sequence number indicates that the current block uses the LFNST, determining a mapping mode of an LFNST transform set according to the MIP parameter; according to the mapping mode of the LFNST transform set, one LFNST transform kernel candidate set is selected from the multiple LFNST transform kernel candidate sets, and an LFNST transform kernel used by the current block is determined from the selected LFNST transform kernel candidate set; and performing conversion processing on the conversion coefficient by using the LFNST conversion kernel.

Embodiments of the present application provide an encoding method, a decoding method, an encoder, a decoder, and a storage medium. The decoding method comprises: determining a prediction parameter of a current block, wherein the prediction parameter of the current block comprises a first indication parameter; if the first indication parameter indicates using a DIMD merge mode to decode the current block, on the basis of one or more candidate positions, determining direction parameters to be merged, wherein the one or more candidate positions are located in a reconstructed area of an image where the current block is located; and determining a predicted value of the current block on the basis of the direction parameters to be merged.

The invention discloses a soft decoding method and device, a medium and a product, and relates to the technical field of error correction coding, and the method is applied to a low-density parity check code, and comprises the steps: obtaining a target low-density parity check code with an information node and a check node containing an erasure bit; and allocating a preset non-zero log-likelihood ratio to the erasure bit on the check node, and executing first soft decoding. And if the first soft decoding fails, judging whether to carry out second soft decoding or not based on the weight of the syndrome generated by the first soft decoding and the number of the erasure bits on the information node. If it is judged that the second soft decoding needs to be carried out, a preset non-zero log likelihood ratio is distributed to the erasure bit located on the information node, and the second soft decoding is carried out. According to the method and the device, the erasing bits on different nodes are conditionally processed in stages, so that the success rate and the efficiency of decoding are effectively improved.

The invention discloses a decoder, an encoder, an image encoding method, an image decoding method and a storage medium, and belongs to the technical field of encoding and decoding. The decoder comprises a first decoding network, a super decoding network and a context network, and the first decoding network comprises a first sub-network, a second sub-network, a third sub-network and a fourth sub-network which are sequentially connected from input to output. The number of channels of the input tensor of the fourth sub-network is greater than the number of channels of the input tensor of the third sub-network, and the number of channels of the input tensor of the fourth sub-network is greater than the number of channels of the input tensor of the second sub-network. By combining the structure of the first decoding network, the channel number of the input tensor of the fourth sub-network is set to be greater than the channel number of the input tensors of the third sub-network and the second sub-network, so that the calculation complexity of the first decoding network can be reduced, and the quality of the image reconstructed by the first decoding network can be ensured not to be obviously reduced.

The embodiment of the invention relates to the technical field of exploration and development, and provides a well logging curve reconstruction method, device and equipment, a storage medium and a product, the method comprises the steps that an original well logging curve in a specified time period is obtained, the original well logging curve comprises a to-be-reconstructed well logging curve and a plurality of basic well logging curves, carrying out representation learning on the original logging curve to obtain an initial feature vector matrix; the initial feature vector matrix is input into a pre-trained curve reconstruction model, a reconstruction curve of the to-be-reconstructed logging curve is obtained, the curve reconstruction model comprises at least one decoding layer, and the decoding layer comprises an asymmetric causal attention layer, a first normalization layer, a feedforward network layer and a second normalization layer; the asymmetric causal attention layer is used for extracting the space-time correlation weight of the initial feature vector matrix. According to the embodiment of the invention, the reconstruction precision of the logging curve can be improved, so that accurate and reliable data support is provided for exploration and development decisions of oil and gas fields.

The invention discloses a multimode code scanning module, which comprises a power supply module, a charging and discharging module, a power supply voltage reduction module, a working mode selection module, a code scanning engine module, a serial port module and a wireless module, and is characterized in that the power supply module is used for introducing a working power supply to the charging and discharging module and the power supply voltage reduction module; the charging and discharging module is used for battery charging and discharging management and providing stable working voltage for other modules, the working mode selection module is used for switching output modes of the code scanning engine module, and the code scanning engine module decodes two-dimensional code data and outputs decoding information. The serial port module is used for outputting the decoding information generated by the code scanning engine module through serial port communication, and the wireless module is used for outputting the decoding information generated by the code scanning engine module through wireless communication. The method has high adaptability and application flexibility, and has high applicability and reliability in special scenes.

An encoding device according to one aspect of the present disclosure comprises a circuit, and a memory connected to the circuit. During operation, the circuit determines whether a first vertex, among a plurality of vertices comprised by a first sub-mesh divided from a three-dimensional mesh, which is not positioned on a side constituting the outer periphery of the first sub-mesh overlaps with a vertex comprised by a second sub-mesh divided from the three-dimensional mesh (S401), and on the basis of the determination result, encodes first information indicating whether the first vertex overlaps with the vertex comprised by the second sub-mesh into a bitstream (S402).

Disclosed in embodiments of the present application are an encoding method, a decoding method, a code stream, an encoder, a decoder, and a storage medium. The decoding method includes: decoding a relevant syntax element of a current block; according to the relevant syntax element, determining to use an intra-template matching prediction (TMP) (IntraTMP) merged intra prediction mode to perform prediction on the current block; determining a matching block of the current block on the basis of a TMP mode, and determining a first predicted block of the current block according to the matching block; determining a second predicted block of the current block on the basis of a non-template matching intra prediction mode; and merging the first predicted block and the second predicted block to determine a final predicted block of the current block.

An encoding method includes: decoding a bitstream to determine prediction parameters of a current block; determining a first prediction block of the current block according to the prediction parameters; determining model parameters according to a first color component value and a second color component value of the first prediction block; determining a reference sample value of a first color component sample of the current block; determining a prediction value of a second color component sample of the current block according to the reference sample value of the first color component sample of the current block and the model parameters; and determining a reconstructed value of the second color component sample of the current block according to the prediction value of the second color component sample of the current block.

The embodiment of the invention provides a model training method, an information recommendation method, equipment, a storage medium and a program product. According to the embodiment of the invention, a multi-encoder-multi-sub-decoder-total decoder hybrid model architecture is provided, sample data of different information modes correspond to different encoders-sub-decoders, and a mode of processing all training sample data by a single model is converted into a divide-and-conquer mode. The internal complexity of each encoder-sub-decoder is relatively low, the complexity of model training can be reduced, resource consumption can be saved, and different encoder-sub-decoders can be trained in parallel, so that the model training time can be shortened; and furthermore, by utilizing a dual decoding mechanism of the sub-decoder and the global decoder, parameters of the encoder can be continuously adjusted through local optimization and global optimization, the performance of the model is optimized, the accuracy of a reasoning result is improved, the convergence speed of the model is accelerated, the model training efficiency is further improved, and the model training time is saved.

The embodiment of the invention discloses a video encoding and decoding method and device, equipment and a medium. The method comprises the following steps: a coding end determines a mode identifier corresponding to a sub-block according to a coding mode of a target transformation block for representing binarization coding distribution of a non-zero transformation coefficient at an internal position of the sub-block, and codes the mode identifier to obtain coding information of the target transformation block, so that the coding end or a decoding end carries out decoding according to the coding information of the target transformation block, and the target transformation block is decoded. And obtaining a coding mode for representing the binarization coding distribution of the non-zero transformation coefficients at the internal positions of the sub-blocks, thereby realizing the determination of the positions of the non-zero transformation coefficients corresponding to the target transformation block. According to the technical scheme, the coding and decoding efficiency of the transform block is improved, and the video coding and decoding reliability is high.

The embodiment of the invention provides a point cloud decoding method, a point cloud encoding method, a decoder and an encoder, and the point cloud decoding method comprises the steps: decoding a code stream of a point cloud, and determining a residual value of attribute information of a target point in the point cloud; determining an initial reconstruction value of the attribute information of the target point based on the residual value of the attribute information of the target point and the predicted value of the attribute information of the target point; determining a filter coefficient of the target point; and filtering the initial reconstruction value of the attribute information of the target point based on the filtering coefficient of the target point, and determining the reconstruction value of the attribute information of the target point. According to the method, the initial reconstruction value of the attribute information of the target point is filtered by using the filtering coefficient of the target point, the decoding performance is improved, and the quality of the reconstructed point cloud is enhanced.

Disclosed herein are a decoding method and apparatus and an encoding method and apparatus for deriving an intra-prediction mode. An intra-prediction mode may be derived using a method for deriving an intra-prediction mode based on a neighbor block of the target block, a method for deriving an intra-prediction mode using signaling of the intra-prediction mode of the target block, or a method for deriving an adaptive intra-prediction mode based on the type of a target slice. An MPM list may be used to derive the intra-prediction mode, and a temporal neighbor block or the like may be used to configure the MPM list.