48 results about "Dual tree" patented technology

The invention discloses a vacuum arc-extinguishing chamber contact surface condition evaluation method and system, and belongs to the technical field of vacuum circuit breakers. According to the method, short-time Fourier transform noise reduction is improved by adopting an adaptive window length, signals are enhanced in combination with dual-tree complex wavelet transform, and data are dynamically normalized by improving K-means clustering; according to the constructed lightweight CRNN model, residual connection and an SE module are introduced into a convolution module, and a bidirectional quasi-recurrent neural network is adopted by a circulation module to capture time sequence features; the mixed loss function is combined with an AdamW optimizer, and the convergence stability is improved through L2 regularization; and dynamically evaluating the ablation degree of the contact based on a fuzzy logic algorithm. According to the method, through time-frequency feature fusion and lightweight network design, high-precision classification of direct-current pre-breakdown waveforms is realized, the problems of degradation, over-fitting and slow convergence of a traditional model are solved, and an intelligent solution is provided for vacuum arc-extinguishing chamber insulation performance evaluation.

Interaction may occur between adaptive dual tree and intra-block copy (IBC). For example, an encoder / decoder may obtain a video block in a slice. An inter prediction may be enabled for the slice. The device may determine a prediction mode that is to be used to encode a video block in the slice. The device may, e.g., based on a determination that the prediction mode is IBC, determine whether a dual tree mode or a single tree mode is to be used to encode the video block. The device may encode / decode the video block based on the determination of whether the dual tree mode or the single tree mode is to be used to encode / decode the video block.

An example device includes a memory and one or more processors. The one or more processors are configured to determine whether to use single-tree coding for a first codec tree unit (CTU), determine a first transform unit (TU) based on a first luma sample transform block (TB) and first two corresponding chroma sample TBs based on the first CTU using the single-tree coding. The one or more processors are further configured to determine whether to use dual-tree coding for a second CTU, determine a second TU based on (I) a second luma sample TB or (II) a second set of two chroma sample TBs based on the second CTU using the dual-tree coding. The first TU includes a syntax structure for transforming the first TB samples, and the second TU includes a syntax structure for transforming the second TB samples.

An electronic device performs a method of decoding video data. The method comprises: receiving, from the bitstream, a plurality of syntax elements associated with an encoding unit, wherein the plurality of syntax elements indicates the encoding tree type of the encoding unit and whether local dual-tree mode is enabled for the encoding unit; and, based on the determination that the encoding tree type of the encoding unit is single-tree and that local dual-tree mode is enabled for the encoding unit; disabling palette mode for the encoding unit when the encoding unit is equal to or smaller than a predetermined threshold.In some modes, disabling palette mode for the encoding unit includes: disabling palette mode for both the luma and chroma components of the encoding unit, or disabling palette mode only for the chroma component of the encoding unit.

The present invention discloses a method and system for evaluating the surface condition of contacts of a vacuum interrupter, which belongs to the technical field of vacuum circuit breakers. The method uses adaptive window length to improve short-time Fourier transform for noise reduction, combines dual-tree complex wavelet transform to enhance signals, and dynamically normalizes data through improved K-means clustering; a lightweight CRNN model is constructed, the convolution module introduces residual connection and SE module, and the recurrent module uses a bidirectional quasi-recurrent neural network to capture time series features; the hybrid loss function is combined with the AdamW optimizer to improve the convergence stability through L2 regularization; and the degree of contact ablation is dynamically evaluated based on a fuzzy logic algorithm. The method achieves high-precision classification of DC pre-breakdown waveforms through time-frequency feature fusion and lightweight network design, solves the problems of traditional model degradation, overfitting and slow convergence, and provides an intelligent solution for the insulation performance evaluation of vacuum interrupters.

A method for decoding the video bit stream includes receiving the video bit stream associated with a coding tree unit (CTU) including a coding unit (CU) at a k-th depth node, identifying a first syntax element from the video bit stream, identifying a second syntax element from the video bit stream, and configuring the video decoder based on these two syntax elements, and decoding the CTU to generate the video data. The CU includes a plurality of coding blocks (CBs). The first syntax element indicates if a CU at a (k+1) th depth node is to be further split by using a dual-tree partitioning method. The second syntax element indicates that a first CB of the CU at the (k+1) th depth node is to be further split and a second CB of the CU at the (k+1) th depth node is not to be further split.

The application discloses a virtual viewpoint image quality evaluation method and system based on double-tree complex wavelet transform. The method comprises the following steps: using an algorithm to perform feature matching on a reference image; performing multi-scale double-tree complex wavelet transform on the matched reference image and a virtual viewpoint image for multiple times to obtain a first wavelet subband set corresponding to the matched reference image and a second wavelet subband set corresponding to the virtual viewpoint image; calculating gradient amplitude similarity between third-level wavelet subbands of the first wavelet subband set and the second wavelet subband set, and using the gradient amplitude similarity to calculate a texture distortion score of the virtual viewpoint image; calculating structural similarity between fifth-level wavelet subbands of the first wavelet subband set and the second wavelet subband set, and using the structural similarity to calculate a structure distortion score of the virtual viewpoint image; and calculating a quality score of the virtual viewpoint image according to the texture distortion score and the structure distortion score. The application can accurately evaluate the quality of the virtual viewpoint image.

To provide methods and apparatuses for video encoding / decoding.SOLUTION: An apparatus for video decoding includes receiving circuitry and processing circuitry. The processing circuitry decodes prediction information of a block from a coded video bitstream, determines whether to allow a palette based coding mode for the block based on a comparison of a size of the block with a threshold, determines whether the block is under a local dual tree structure based on the prediction information, and decodes the block based on the determination of whether to allow the palette based coding mode for the block and the determination of whether the block is under the local dual tree structure.SELECTED DRAWING: Figure 11

The invention provides a dual-tree collaborative HS coding intelligent matching method and device. The method comprises the steps of performing standardization processing on commodity information, and based on the standardized commodity information and structured attribute information, retrieving from a preset HS knowledge base to generate a candidate HS code set; performing branch constraint on the candidate HS code set according to the annotation rule data to obtain at least one compliance candidate subset and a corresponding discrimination attribute missing set; for the compliance candidate subsets, calling a data-driven decision tree to score and sort candidate HS codes in the compliance candidate subsets to obtain at least one target HS code and confidence; and when the confidence coefficient is lower than a preset threshold value and the judgment attribute missing set is non-null, generating supplementary inquiry information for distinguishing candidate HS codes in the compliance candidate subset based on split judgment information of the data-driven decision tree on the compliance candidate subset. According to the method, the HS code matching accuracy can be improved, the compliance interpretability is enhanced, and the manual completion cost is reduced.

Adaptive dual tree coding may be optimized, for example, to implement a trade-off between compression efficiency and encoder complexity. For example, adaptive dual tree / single tree representation in inter slices may be conditioned on characteristics of the slice / picture, e.g., slice type, temporal layer id, and / or temporal depth of the slice being coded / decoded. Use of block-vector guided convolutional cross-component model (BVG-CCCM) may be conditioned on disabling adaptive dual tree and / or characteristics of the slice being encoded / decoded. Use of multi-type tree (MTT) split modes early termination may be conditioned on disabling of adaptive dual tree. In examples, a device (e.g., decoder / encoder) may determine a hierarchical parameter associated with a slice. The device may determine whether to enable a dual tree mode for the slice based on the hierarchical parameter for the slice. The device may decode the slice based on the determination of whether to enable the dual tree mode for the slice.

The present invention relates to an image encoding / decoding method and device. The image decoding method according to one embodiment of the present invention comprises the steps of: determining a tree type of the current unit included in the current slice; dividing a luminance block of the current unit into sub-luminance blocks on the basis of the tree type; and dividing a chrominance block of the current unit into sub-chrominance blocks on the basis of the tree type, wherein the tree type of the current unit is determined as either a single tree or a dual tree, and the current slice is one from among an I slice, a B slice and a P slice.

Disclosed herein are systems, methods, and instrumentalities associated with dual tree coding modes and chroma intra prediction modes reordering. A video coding device as described herein may determine whether a chroma video block is located in an intra-coded region of an inter-coded video slice. Based at least on a determination that the chroma video block is located in the intra-coded region of the video slice and a further determination that a dual tree partition mode is enabled for the intra-coded region, the video coding device may be further configured to determine a plurality of intra prediction modes for the chroma video block, calculate, for each of plurality of intra prediction modes, a respective combined cost associated with predicting the chroma video block and a luma video block co-located with the chroma video block using the intra prediction mode, and reorder the plurality of intra prediction modes based on the respective combined cost calculated for each of the plurality of intra prediction modes. The video coding device may then code the chroma video block based on the reordering of the plurality of intra prediction modes.

The invention discloses a dual-tree genetic programming method for processing a long-tail image classification problem, and the method comprises the following steps: constructing a dual-tree genetic programming individual which comprises a data enhancement tree and a feature extraction tree; setting a staged sampler; performing a multi-generation evolution process, wherein each generation comprises population initialization, individual fitness evaluation, selection, crossover and mutation operation; after the evolution is finished, outputting a dual-tree individual with the highest fitness as a final classification model for classifying a new image; the method is simple and efficient in model deployment and has practical value.

A video decoding device may determine an inverse transform for an intra chroma block based on dual tree usage associated with the intra chroma block. An inverse transform may be performed for the intra chroma block based on the determined inverse transform. The video coding device may enable a non-separable transform for the intra chroma block if the intra chroma block belongs to a region in local dual-tree mode. The inverse transform may be determined based on the non-separable transform being enabled. A video encoding device may determine to use local dual-tree mode in a region. The device may, for a chroma block in the region, evaluate a non-separable transform. The device may select a transform based on the evaluation. The device may perform transformation on the chroma block based on the selected transform. The non-separable transform may be a low-frequency non-separable transform (LFNST) or a non-separable primary transform (NSPT).

The present invention relates to a ground-penetrating radar signal denoising method that combines two-dimensional VMD with DT-CWT. The method first performs one-dimensional VMD on the original two-dimensional ground-penetrating radar noisy data in the time dimension, removes the intrinsic modal components corresponding to the noise according to corresponding judgment criteria, and then reconstructs the data. The reconstructed data is then subjected to one-dimensional VMD in the spatial dimension, and the intrinsic modal components corresponding to the noise are removed and then reconstructed. The reconstructed data after the two-dimensional VMD denoising process is subjected to a discrete dual-tree complex wavelet transform, and a corresponding threshold formula is selected for threshold denoising. The data is then reconstructed by inverse dual-tree complex wavelet transform to obtain the denoised data. This method takes into account the noise distribution of the data in the spatial dimension, performs two-dimensional VMD denoising on the original noisy data, and effectively improves the data signal-to-noise ratio. At the same time, to further improve the data signal-to-noise ratio, a dual-tree complex wavelet transform that can achieve precise reconstruction is used to perform secondary denoising on the data.

The application belongs to the technical field of computer vision and computer graphics, and discloses a multi-view three-dimensional reconstruction method based on cross-domain feature fusion, equipment and medium, the method comprises the following steps: cross-feature domain coding is carried out on the initial feature token generated by multi-angle images, the coding decomposes the feature into low-frequency and high-frequency components through dual-tree complex wavelet transform, and the amplitude modulation is carried out on the high-frequency component to enhance the details, and the space-frequency fusion feature is generated; the space-frequency fusion features of the multi-angle are weighted and merged through variance embedding, the weight is generated by calculating the variance of each feature token, and adaptive weighted clustering is carried out based on the weight to generate the fused multi-angle feature; three-source attention decoding is carried out on the fused feature, the static embedding is taken as the query, the space-frequency fusion feature is taken as the key, and the fused multi-angle feature is taken as the value, cross-domain attention calculation and up-sampling are carried out, and finally the three-dimensional voxel reconstruction result of the target object is generated.

Methods, systems and apparatus for video processing are described. One example video processing method includes performing a conversion between a video comprising a video block and a bitstream of the video according to a rule, wherein the video block is a coding tree node that includes one or more coding units, and wherein the rule specifies that a coded information of the video block is indicative of whether a coding mode is enabled for the one or more coding units of the video block.

The present invention discloses an OBN data denoising method and related device. The method comprises: performing a dual-tree complex wavelet transform on the P component data and the Z component data respectively; matching the amplitude spectrum of the Z component data according to the maximum amplitude of the amplitude spectrum of the P component data to obtain the amplitude spectrum amplitude value of the Z component data that matches the P component; calculating the amplitude spectrum of the Z component data after amplitude matching; calculating the amplitude matching coefficient according to the amplitude spectrum of the Z component data after amplitude matching; calculating the complex wavelet coefficient of the Z component data after amplitude matching according to the amplitude matching coefficient; performing a dual-tree complex wavelet inverse transform on the complex wavelet coefficient of the Z component data after amplitude matching to obtain the denoised Z component data. The present invention can significantly suppress Vz noise in the Z component data, and the signal-to-noise ratio of the denoised Z component gather data and stacked profile is significantly improved.

A compressed bitstream is received. A first syntax element is decoded from the compressed bitstream, indicating whether a luma block and a chroma block associated with a coding unit are to be split using a single tree or a dual tree. The single tree refers to a partitioning structure where the luma block and the chroma block have the same partitioning, and the dual tree refers to a partitioning structure where the luma block and the chroma block have different partitionings. Based on the first syntax element, the luma block and the chroma block are split.

To provide methods and apparatus for video encoding / decoding.SOLUTION: An apparatus for video decoding includes receiving circuitry and processing circuitry, wherein the processing circuitry decodes prediction information of a block from a coded video bitstream, determines whether to allow a palette-based coding mode for the block based on a comparison of a size of the block and thresholds, determines whether the block is under local dual tree structure based on the prediction information, and decodes the block based on the determination of whether to allow the palette-based coding mode for the block and the determination of whether the block is under local dual tree structure.SELECTED DRAWING: Figure 11

The invention discloses a data enhancement method based on dual-tree complex wavelet transform, and mainly solves the problems that a non-stationary signal data enhancement method in the prior art lacks multi-scale analysis capability, cannot fully retain local key features and is insufficient in model generalization capability. According to the scheme, the method comprises the following steps: 1) preprocessing an original signal to enable the original signal to meet the input requirement of dual-tree complex wavelet transform (DTCWT); 2) performing multi-scale decomposition on the signal by adopting DTCWT, and separating a low-frequency approximate component and a high-frequency detail component; 3) selecting a random zero sequence to replace the RZSR or a random noise sequence to replace the RNSR according to an enhancement requirement; 4) generating a random sequence, replacing high-frequency detail components, and meanwhile, retaining low-frequency components; and 5) reconstructing the signal through the inverse DTCWT, generating an enhanced signal, and outputting an enhanced signal. The method can effectively enhance the diversity of data, retains the global characteristics and local detail characteristics of signals, and can be used in the technical field of wireless communication.

This invention discloses a motor fault diagnosis method based on a large language model, belonging to the field of motor fault diagnosis. The method includes: first, collecting three-phase current data; then, using dual-tree complex wavelet transform to extract the amplitude and phase information of multi-layer complex wavelet coefficients as signal fault features, avoiding manual feature selection; next, constructing a multi-layer feature extraction and hierarchical weighted domain adversarial collaborative training framework that integrates grouping and Browsing optimization to extract multi-scale features and enhance domain invariance, thereby improving cross-condition generalization ability; finally, aligning the extracted signal embedding and text embedding across modalities through category-level comparative learning, and fine-tuning the large language model to recognize signal modes. This invention improves fault classification accuracy while enhancing model generalization and achieving textual semantic interpretation of diagnostic results.

Video processing methods, systems, and apparatus are described. One example method includes performing conversion between a video block of a video and a bitstream of the video using a palette mode in which samples of the video block are represented using a palette of representative color values. A size of the palette for the video block is determined based on whether a local dual tree is applied to the conversion.

The application provides a dual-tree collaborative HS coding intelligent matching method and device. The method comprises: standardizing commodity information, retrieving a candidate HS coding set from a preset HS knowledge base based on the standardized commodity information and structured attribute information; performing branch constraint on the candidate HS coding set according to annotation rule data to obtain at least one compliant candidate subset and a corresponding missing attribute set; for the compliant candidate subset, calling a data-driven decision tree to score and sort the candidate HS coding in the compliant candidate subset to obtain at least one target HS coding and a confidence level; when the confidence level is lower than a preset threshold and the missing attribute set is not empty, generating supplementary inquiry information for distinguishing the candidate HS coding in the compliant candidate subset based on the split discrimination information of the data-driven decision tree on the compliant candidate subset. The application can improve the HS coding matching accuracy, enhance the compliance interpretability, and reduce the artificial completion cost.

The application provides a PE pipeline multi-source signal denoising method based on a dual-tree complex wavelet transform, and belongs to the technical field of signal denoising, and the method comprises the following steps: S1, multi-source signal acquisition and pretreatment; S2, signal collaborative calibration; S3, dual-tree complex wavelet decomposition; S4, noise level estimation; S5, adaptive threshold denoising; S6, signal reconstruction; S7, effect evaluation and optimization. The application adopts a single pendulum wave signal as a benchmark signal, and assists in time synchronization and frequency calibration, thereby improving the accuracy of signal processing, effectively suppressing various noise interferences, and significantly improving the signal-to-noise ratio (SNR) of the denoised signal.

Cross-component convolution mode (CCCM) may be enabled for a chroma prediction unit (PU) in a coding tree unit (CTU) with dual tree mode enabled. A device may determine a luma PU collocated with the chroma PU. The device may determine a set of reference luma samples associated with the chroma PU. The device may generate a modified set of reference luma samples by adding to the set of reference luma samples padding luma samples generated based on the set of reference luma samples. Padding luma samples may not be replaced by a previously reconstructed luma sample in the CTU. The device may generate a CCCM filter coefficient based on the modified set of reference luma samples. The device may predict the chroma PU based on the CCCM filter coefficient and the luma PU. The device may decode the CTU based on the predicted chroma PU.

The invention discloses a power plant operation robot low-distortion path planning method based on hybrid weighted RRT, and the method comprises the following steps: S1, power plant environment modeling and target setting; s2, performing dual-tree mixed search to generate an initial solution; s3, combining the double trees; s4, single-tree weighted optimization is carried out; s5, path smoothing processing is carried out; and S6, outputting a final navigation path. According to a specific scene of a power plant operation robot, low-distortion path planning is realized through mixed weighted RRT, dual-tree search and single-tree weighted optimization are fused, path curvature continuity is controlled, equipment protection and safety constraints of a power plant are adapted, a low-distortion path is realized, and motion stability of the robot is guaranteed.

An electronic apparatus performs a method of decoding video data. The method includes: receiving, from the bitstream, a plurality of syntax elements associated with a coding unit, the plurality of syntax elements indicating the coding tree type of the coding unit, and whether the local dual tree mode is enabled for the coding unit; and in accordance with the determination that the coding tree type of the coding unit is a single tree, and the local dual tree mode is enabled for the coding unit: disabling the palette mode for the coding unit when the coding unit has the size equal to or less than a predefined threshold. The disabling palette mode for the coding unit may include: disabling the palette mode for both the luma component and chroma component of the coding unit, or disabling the palette mode for only the chroma component of the coding unit.

This invention discloses a method for diagnosing rolling bearing faults, including experimental setup, signal reconstruction, model extraction, fault diagnosis, and verification. The method involves building a rolling bearing fault simulation experimental setup and collecting the original vibration signals from the setup. A dual-tree complex wavelet packet transform is used to decompose the vibration signals into high-frequency wavelet coefficients. Threshold denoising is then applied to these high-frequency wavelet coefficients, and the denoised wavelet coefficients are reconstructed to obtain the denoised reconstructed signal. A cyclic spectrum coherence two-dimensional feature extraction model is established for the reconstructed signal. A multi-scale convolutional layer parallel structure is built using multi-scale convolutional kernels to extract input features at different scales. A multi-scale convolutional neural network is constructed for fault type diagnosis, and the diagnostic accuracy is determined. The diagnostic accuracy of the input and output shaft bearings under different operating conditions is compared to verify the stability and generalization ability of the method. This invention can improve the accuracy of rolling bearing fault diagnosis and has excellent generalization ability.