2552 results about "Coding block" patented technology

The invention discloses a remote sensing image semantic segmentation-oriented spatial spectrum context feature enhancement method and device. The method comprises the following steps of: constructing a neural network model based on an encoder-decoder architecture; inputting the preprocessed remote sensing image set into a feature coding block, and extracting hierarchical features; according to the model, spectrum attention and position self-attention mechanisms are integrated through a collaborative attention module, and the sensitivity of network spectrum and spatial context information is remarkably enhanced; the network coding module efficiently compresses and codes the features before entering a decoding stage; a cross fusion module is applied to intelligently fuse features between a coding block and a decoding block to ensure that information is not lost in a decoding process; the feature map is mapped into a pixel-level category label through a Softmax layer, precise semantic segmentation is achieved, and a high-quality classification result is obtained. According to the method, through collaborative modeling of the spectrum and the spatial context, high-frequency details are effectively reserved, and the precision of semantic segmentation is improved.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a neuromorphic visual target tracking method and system based on image processing, and relates to the technical field of neuromorphic calculation, and the method comprises the steps: fusing the input of an event camera and a conventional image sensor, constructing a combined input tensor, and introducing a multi-scale convolution and synaptic event driving mechanism. Quick response and stable feature extraction of a high-speed moving target are realized, and coding block mistaken deletion and tracking loss caused by quick movement of the target are effectively avoided, so that system delay is reduced. Meanwhile, in combination with significance entropy difference evaluation and a dynamic brightness enhancement mechanism, the target judgment accuracy under low illumination and complex backgrounds is improved; redundant noise blocks are screened out through a significance weight function and confidence calculation, the redundancy calculation burden is relieved, and the lightweight characteristic of the system is guaranteed. A memory trajectory tensor and dynamic template adjustment mechanism based on a recurrent neural network is further introduced, time sequence consistency verification and self-adaptive updating are achieved, and the stability and robustness of the tracking process are enhanced.

Systems, methods, and computer-readable storage media for providing a composable cyber resilience object. A method can include identifying, by one or more processing circuits, a posture state of at least one entity, generating or selecting a first plurality of code blocks corresponding with a parameters of at least one third-party, and determining the entity qualifies for protection based on the posture state and the rules or conditions. The method can include generating or selecting a second plurality of code blocks including functions to provide the protection based on the rules or conditions and generating the composable cyber resilience object by integrating a portion of the first plurality of code blocks and the second plurality of code blocks into at least one data structure. The method can include linking the composable cyber resilience object and a computing or networking infrastructure of the entity using a communication interface or structure.

An apparatus may include a transmitter and one or more processors. The one or more processors may identify, based on a first parity check matrix of a first quasi-cyclic-low-density parity-check (QC-LDPC) code according to a code rate of 3 / 4, a second parity check matrix corresponding to a first exponent matrix comprising 576 values for a second QC-LDPC code. The second QC-LDPC code may have a code block size that is twice a code block size of the first QC-LDPC code. The one or more processors may encode data using the second parity check matrix. The transmitter may be configured to transmit the encoded data.

Methods, apparatuses, and non-transitory computer-readable storage media are provided for video coding. In one method, a decoder derives a first and a second reference pictures for a current coding block; the decoder derives a first and a second predictor samples based on a motion vector associated with the first reference picture using a motion compensation process from the first reference picture; the decoder determines whether the first and the second predictor samples are out-of-boundary (OOB), and in response to determining the first or the second predictor sample is OOB, the decoder replaces the first or the second predictor sample that is OOB with a first or a second alternative predictor sample; and the decoder generates the final prediction sample by averaging sample values of the first predictor sample and the second predictor sample.

A method of decoding coding units of a coding tree for an image frame from a video bitstream comprising splitting a region of the coding tree into a plurality of coding blocks, each of the coding blocks including a prediction block. Determining matrix intra prediction flags for the prediction block of each of the coding blocks, the determination based upon (i) an area of the region if the region meets a threshold, or (ii) a budget for the region if the area of the region does not meet the threshold. The method further comprises reading matrix coefficients from a memory for each prediction block determined to use matrix intra prediction according to the determined flag; and decoding the coding units using prediction blocks generated for each coding unit in the region using reference samples of each prediction block and the matrix coefficients.

The invention discloses a code translation method and system, electronic equipment and a computer readable storage medium, which are applied to a code translation model, and the code translation method comprises the following steps: generating an abstract syntax tree corresponding to a source code; segmenting the source code according to the code structure of the abstract syntax tree to obtain a plurality of code blocks; matching a corresponding code mapping relationship in a code mapping library; translating the plurality of code blocks into a plurality of target code blocks of a target code language according to a code mapping relationship; and compiling the plurality of target code blocks into target code in a target code language. According to the code translation model, the abstract syntax tree corresponding to the source code is firstly generated, then the whole source code is segmented into the multiple code blocks based on the abstract syntax tree, therefore, the whole task is segmented, then code translation is conducted through the code mapping relation in the code mapping library, the transfer speed and efficiency are improved, and the code translation efficiency is improved. And finally, compiling the plurality of translated target code blocks into a whole section of target code to ensure the integrity and accuracy of compiling.

The invention discloses a medical image segmentation method and system based on a hierarchical pre-training model, and the method comprises the steps: carrying out the size adjustment of an input image, and carrying out the data enhancement operation; extracting multi-scale features of the medical image by using an encoder based on a hierarchical pre-training visual model, and inserting an adapter in front of each encoding block; a decoder based on a dense connection structure is adopted to gradually recover the spatial resolution, a feature enhancement module is applied behind each decoder block for feature enhancement, and dense connection is achieved through layer-by-layer up-sampling and cross-layer connection; multi-scale supervision and prediction are realized through three output heads, a main output head generates a main segmentation result, and two auxiliary output heads respectively generate segmentation results from an intermediate decoding layer to provide a multi-scale supervision signal. Therefore, the problems of precision, accuracy and efficiency of an existing medical image segmentation technology in tiny focus recognition are solved, and the recognition capability of tiny boundaries and complex geometrical shapes is remarkably improved.

An apparatus may include a transmitter and one or more processors. The one or more processors may identify, based on a first parity check matrix of a first quasi-cyclic-low-density parity-check (QC-LDPC) code according to a code rate of 5 / 6, a second parity check matrix corresponding to a first exponent matrix comprising 384 values for a second QC-LDPC code. The second QC-LDPC code may have a code block size that is twice a code block size of the first QC-LDPC code. The one or more processors may encode data using the second parity check matrix. The transmitter may be configured to transmit the encoded data.

Embodiments of the present disclosure relate to the field of video coding and decoding, and provide a picture decoding method, a picture coding method, and corresponding apparatuses. According to an example of the picture decoding method, a quantization parameter (QP) value of at least one pixel point is determined for any at least one pixel point indicating one pixel point or a plurality of parallel dequantized pixel points in the current coding block, the QP values of at least two pixel points among pixel points in the current coding block being different. The at least one pixel point is then dequantized according to the QP value of the at least one pixel point. The QP value of each pixel point is determined for the coding block; therefore, each pixel point can be dequantized according to the QP value of each pixel point.

Systems, methods, and instrumentalities are disclosed for template based cross component linear model / multimode linear model (CCLM / MMLM) adjustment. In an example, a device, such as a video decoding device, or a video encoding device, may obtain a prediction model for predicting a coding block. The device may select an adjustment model, from multiple adjustment models, for adjusting the prediction model. The device may adjust the prediction model based on the selected adjustment model. The device may process (e.g., encode and / or decode) the coding block based on the adjusted prediction model.

The system securely executes code blocks for artificial intelligence (AI) agents by creating nano sandboxes in which customer scripts execute. An input is received that causes an agent executor to execute an AI agent. The AI agent can be defined to include a code block for executing a customer script. To securely execute the customer script while preventing unauthorized access on an AI platform, the agent executor can create a nano sandbox in which the customer script of the code block will execute using read-only system resources and files. The agent executor can wrap the customer script in logic that seeds an input variable from a file in the nano sandbox. Execution results in writing to an output file, from which an output is retrieved and returned to the user device. The nano sandbox can then be destroyed.

The invention provides a code retrieval method and device and related equipment, and relates to the technical field of retrieval. The method comprises the following steps: segmenting each source code file to obtain a plurality of code blocks of each source code file; determining description information of each code block, and determining an association relationship between any two code blocks; generating a multi-layer code knowledge graph based on the description information of each code block and the incidence relation between any two code blocks; obtaining query information of a user, and determining a first code block based on the query information; determining a second code block related to the first code block in the multi-layer code knowledge graph; and generating a retrieval result by using the first code block and the second code block. Through the technical means, the problem of low code retrieval accuracy in related technologies is solved.

Methods for video decoding and encoding, apparatuses and non-transitory computer-readable storage media thereof are provided. In one method for video decoding, a decoder may obtain a plurality of prediction blocks based on a current inter coding block; obtain a current template of the current inter coding block, wherein the current template comprises a plurality of reconstructed samples neighboring to the current inter coding block; obtain a plurality of template predictions of the current template respectively corresponding to the plurality of prediction blocks of the current inter coding block; obtain at least one filter based on the plurality of template predictions and the current template; and obtain a filtered block based on the at least one filter and the plurality of prediction blocks.

The invention provides a space-time load prediction method based on a personalized federal map learning Transform in a multi-edge system. The space-time load prediction method comprises the following steps: step 1, constructing a multivariable sequence inversion Transform as a load prediction model of an edge node; 2, designing a PFG, and generating personalized model parameters and spatial features for each edge node through a super network and a graph neural network GNN; the parameters are updated and transmitted to an FL server to calculate parameter changes of the prediction model, and the FL server updates other parameters, super network parameters and node feature vectors of the global model according to the parameters returned by the client; and step 3, combining the MIT and the PFG to form a PFG former, and generating a personalized load for each edge node for prediction. According to the technical scheme, the coding block and the multi-layer perception processing prediction task are used, complicated decoding blocks are abandoned, the prediction precision is improved, and the model parameter quantity is reduced.

An apparatus may include a transmitter and one or more processors. The one or more processors may identify, based on a first parity check matrix of a first quasi-cyclic-low-density parity-check (QC-LDPC) code according to a code rate of 2 / 3, a second parity check matrix corresponding to a first exponent matrix comprising 768 values for a second QC-LDPC code. The second QC-LDPC code may have a code block size that is twice a code block size of the first QC-LDPC code. The one or more processors may encode data using the second parity check matrix. The transmitter may be configured to transmit the encoded data.

Hybrid automatic repeat request (HARQ) processes may be transmitted via configured grants as well as scheduled grants. The configured grants may include time and frequency resources, and transmissions may occur across contiguous transmissions. HARQ process information, such as HARQ IDs and redundancy versions, may be communicated via a control channel, and the control channel may be multiplexed with the transmission resources of the configured grants. Retransmission timers may be used for HARQ processes conveyed via configured grants, and the transmitting apparatus may signal to a receiver when to send an acknowledgement. An acknowledgement may take the form of bitmaps for code block groups of a HARQ. A configured grant may be selected from among multiple configured grants based upon low latency, for example. A group of configured grants may be activated or deactivated via a single command.

The invention relates to the technical field of image processing, discloses an image deblurring method and system based on a UNet structure, and aims to solve the problems of many model parameters and poorer deblurring effect of an existing method. The scheme mainly comprises the following steps: inputting a blurred image into a feature extraction module for down-sampling and feature extraction to obtain blurred image features; inputting the blurred image features into an encoder for encoding operation; a feature attention module is inserted between the coding blocks, and the feature attention module adaptively adjusts the attention on different image features by using a Ghost module and a convolutional layer; the encoded blurred image features are input into a feature fusion module for adaptive feature fusion; the self-adaptive feature fusion result is input into a decoder for up-sampling, and a decoding result is obtained; and carrying out pixel-by-pixel superposition fusion on the blurred image features and the decoding result to obtain a deblurred image. The deblurring effect is improved, the model parameters are reduced, and the method is particularly suitable for industrial scenes with limited resources.

The invention provides a script preservation method which can be applied to the technical field of artificial intelligence. The script preservation method comprises the following steps: carrying out semantic understanding on demand related files by utilizing a large model, extracting core elements, and generating a structured demand change list; analyzing to obtain an abstract syntax tree of an existing script code, and constructing a mapping relationship between the software automation test element and a script code block; dynamically comparing the structured demand change list with an existing script code structure tree based on a mapping relation between software automation test elements and script code blocks, identifying a script range influenced by demand change, and outputting a change influence matrix; and based on the change influence matrix, generating an automatic script code snippet needing to be updated, and realizing preservation of the automatic script. The invention further provides a script preservation device and equipment, a storage medium and a program product.

An apparatus may include a transmitter and one or more processors. The one or more processors may identify, based on a first parity check matrix of a first quasi-cyclic-low-density parity-check (QC-LDPC) code according to a code rate of 1 / 2, a second parity check matrix corresponding to a first exponent matrix comprising 1152 values for a second QC-LDPC code. The second QC-LDPC code may have a code block size that is twice a code block size of the first QC-LDPC code. The one or more processors may encode data using the second parity check matrix. The transmitter may be configured to transmit the encoded data.

The embodiment of the invention provides a data retransmission method, device and system. According to the embodiment of the invention, retransmission is carried out on a physical layer based on a data slice, the data slice comprises a code block carried by at least one FEC code word, and a corresponding serial number is allocated to each data slice in data. A sending device can store sent data slices and corresponding serial numbers in a buffer area while sending data. And after receiving the data, the receiving equipment distributes a corresponding serial number for each data slice according to the same way as the sending equipment. And furthermore, the receiving equipment sends a retransmission request carrying the serial number corresponding to the data slice after finding the uncorrectable error, and the sending equipment extracts the corresponding data slice from the buffer area according to the retransmission request and starts retransmission. It can be seen that the number of code blocks borne by the data slices is small, and compared with message-based retransmission, retransmission based on the data slices is more beneficial to reducing the transmission delay of retransmission and reducing the space of a buffer area.

The invention provides an intelligent instruction execution method, system and device and a medium. The intelligent instruction execution method comprises the steps that current environment state information of a robot and a natural language task instruction input by a user are obtained; generating cue words at least based on the environment state information, the task instruction, a predefined standardized function interface document and a thinking chain example, and inputting the generated cue words into a large language model; the method comprises the following steps: decomposing a task instruction into sub-task sequences by utilizing a large language model, and organizing the decomposed sub-task sequences into complete executable code blocks; performing static logic verification on the code blocks before code execution; if verification is not passed, error description is generated and fed back to the large language model for code correction; and in a code execution stage, if abnormal information is returned after the code is executed, the abnormal information is returned to the large language model, so that the large language model regenerates a correction code according to an abnormal reason. The autonomous decision-making level and the task execution success rate of the robot are improved.

The invention relates to the technical field of automatic testing, and discloses an automatic testing scheme generation method and device and a medium, and the method comprises the steps: matching a demand action in a test demand with a code entry name corresponding to a code segment, and determining a code risk level of a current demand code block; analyzing the code change frequency and the code dependency degree of the current demand code block according to historical test records in the test domain knowledge base, and determining the test dynamic priority of the current demand code block; constructing a control flow diagram and a data flow diagram of the current demand code block, and detecting risk nodes in the control flow diagram and the data flow diagram; generating a test scene of the current demand code block according to the risk node, and generating a boundary value test rule according to a key constraint condition in the data flow diagram; and querying an environment simulation rule of the current demand code block, and packaging the test scene, the boundary value test rule and the environment simulation rule into an automatic test scheme. According to the invention, the code coverage when the test scheme is generated can be improved.

Systems, methods, and instrumentalities are disclosed for most probable mode (MPM) list generation with template-based intra mode derivation (TIMD). An example method involves determining an intra coding mode derivation process is enabled for a first coding block; based on the intra coding mode derivation process being enabled for the first coding block, generating a first MPM list for the first coding block based on a first MPM list generation process; decoding the first coding block based on the first MPM list; determining that the intra coding mode derivation process is disabled for a second coding block; based on the intra coding mode derivation process being disabled for the second coding block, generating a second MPM list for the second coding block based on a second MPM list generation process, different from the first MPM list generation process; and decoding the second coding block based on the second MPM list.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses a version updating method and device, equipment and a storage medium, and relates to the technical field of version updating, and the version updating method comprises the following steps: obtaining to-be-updated version information of to-be-updated software, intercepting an original structured query language (SQL), and generating a syntax tree corresponding to the original SQL, the to-be-updated version information comprises to-be-updated SQL and to-be-updated code blocks; according to the to-be-updated SQL, performing field updating on the syntax tree and then converting to generate a target SQL; according to the code task identifier of the to-be-updated code block, determining a code position of an original code block, and generating a target code; based on the target SQL and the target code, version updating and testing are conducted on the software to be updated, and a version updating task is completed. According to the method, a low-code platform can be helped to accurately identify data and code change ranges, codes and scripts are automatically combined, and the purpose of reducing version updating time is achieved.

The invention discloses a method and device for repairing codes in a memory, a storage medium, a chip and a computer program product, and the method comprises the steps: during starting, each target code block in a first memory is executed in sequence, and the target code blocks are obtained by dividing to-be-executed codes in the first memory in advance; when the target code block in the first memory is started to be executed every time, judging whether the target code block contains a code to be repaired or not; if the judgment result is yes, determining a target storage address of a mapping code block corresponding to the target code block in a second memory according to a preset address mapping relation, and skipping to the target storage address in the second memory to execute the mapping code block, and then jumping back to the first memory and continuing to execute the next target code block until it is confirmed that all the to-be-executed codes in the first memory are executed. According to the scheme, more efficient code repair can be realized in a lower storage space.

In some implementations, an apparatus may include a transmitter and one or more processors. The one or more processors may be configured to identify, according to a code rate of 1 / 2 and a code block size of 3888 bits, a first binary parity check matrix for a quasi-cyclic-low-density parity-check (QC-LDPC) code. The first binary parity check matrix may correspond to a first exponent matrix having 288 values. The one or more processors may be configured to encode data using the first binary parity check matrix. The one or more processors may be configured to transmit the encoded data.

The invention discloses a signal processing method, device and system, and relates to the technical field of communication. In the method, a signal to be transmitted is encoded to obtain a plurality of code blocks, and the plurality of code blocks not only comprise a first data signal and / or a first control signal, but also comprise a management signal, so that the signal types included in the plurality of code blocks are rich. In addition, according to the method, a plurality of code blocks are transmitted through one serial channel, and the number of pins of the serial channel can be small. In addition, the method can adopt a serial channel realized based on the MII, so that the method can be applied to the scene of the MII.