13 results about "Correction technique" patented technology

Systems and methods for dynamic error resolution in hybrid quantum-classical computing environments are disclosed. A system can obtain telemetry data corresponding to a processing job. The system can determine that an error resolution technique is to be applied to the quantum portion of the processing job. The system can select, for a quantum portion of the processing job, the error resolution technique from a plurality of error correction techniques and a plurality of error mitigation techniques. The system can update a hierarchical data structure representing the processing job as at least a set of nodes. The hierarchical data structure can be updated to include the error resolution technique in association with a respective node of the hierarchical data structure representing the quantum portion of the processing job.

The invention discloses a micro-morphology measuring and modeling method for a cutting edge of a light shielding ring of a light shielding cover, and belongs to the technical field of precision measurement and three-dimensional modeling. The method comprises the following steps: firstly, acquiring three-dimensional point cloud data of a cutting edge of a light blocking ring through a laser scanning confocal microscope; carrying out denoising processing on the data by adopting wavelet threshold denoising and five-point secondary smoothing filtering; the data precision is improved by combining clamp installation optimization and inclination correction technologies; data pruning is achieved through curvature analysis, and a cutting edge feature area is extracted; missing data are repaired by using cubic B-spline interpolation; and finally, a high-precision cutting edge model is established through trapezoid fitting, arc fitting and NURBS curved surface reconstruction methods. According to the method, the problem that the micro-morphology representation accuracy of the cutting edge of the light shielding ring of the light shielding cover is insufficient in the prior art is solved, the accuracy and efficiency of the morphology representation of the cutting edge are remarkably improved, and technical support is provided for the surface morphology design of a high-precision light shielding cover.

This paper proposes a low-complexity, hardware-friendly technique for video decoding systems to mitigate striping artifacts while maintaining compression efficiency. Generally, the proposed technique consists of two stages: a striping detection stage and a destripping stage. The striping detection stage identifies potential striping artifact regions in the image / video based on gradient information and other data. The destripping stage applies correction techniques to these identified regions. In one implementation, the destripping modifies the filtering logic proposed by previous video decoding standards for other filtering applications to mitigate striping. When implemented on the AVI video decoding standard and the AOM Video Model (AVM) reference software, the proposed technique significantly improves subjective quality at a reasonable hardware implementation cost. The methods and implementations presented in this document can be beneficially applied to various image / video decoding standards and systems.

Techniques for performing speaker error correction are described. In some examples, speaker error correction is a post-processing task to be performed on aligned predicted words and predicted one or more speaker identities to jointly perform speaker identities error correction and at least inverse text normalization, wherein the post-processing at least includes: predicting word and speaker contextual features from the aligned predicted words and predicted one or more speaker identities using an encoder, and predicting, from the word and speaker contextual features, inverse text normalization of the aligned predicted words and corrected speaker identities using a decoder.

Techniques for positioning are disclosed. In an aspect, a positioning entity determines an expiration time for applying correction data to positioning measurements of one or more transmission points (TPs) (610), applies the correction data to one or more positioning measurements of one or more TPs obtained by a user equipment (UE) prior to expiration of the expiration time to determine one or more corrected positioning measurements (620), and determining an estimate of a position of the UE based at least in part on the one or more corrected positioning measurements (630).

This invention discloses a method and system for managing and analyzing medical report data in hematological diseases, belonging to the field of medical information processing technology. The system includes: S1, data acquisition and fingerprint generation; S2, time-series reconstruction and correction; S3, semantic parsing and standardization; S4, feature coupling and secure computation; and S5, report generation and audit updates. This invention utilizes a time-frequency domain dual-domain correction technique, which effectively eliminates periodic errors and fluctuations between different data sources and different acquisition time points, improving the accuracy and consistency of data processing. This correction method goes beyond traditional time alignment; it identifies and removes periodic interference in the signal through frequency domain analysis, ensuring time-series consistency between different sources. This ensures that even with multi-source data, the analysis results maintain high accuracy and reliability, avoiding erroneous diagnoses and recommendations due to data errors, thus providing a more accurate and reliable basis for clinical decision-making.

To provide a color shift correction technique in consideration of variation in frictional force between a photoreceptor and an intermediate transfer body.SOLUTION: The image forming apparatus includes an image forming unit configured to form an image based on a print job on a sheet by forming images with toners of different colors on a plurality of photoconductors that are rotationally driven, respectively, and transferring the images formed on the plurality of photoconductors to the sheet via an intermediate transfer member that is rotationally driven, a detection unit configured to detect the image formed on the intermediate transfer member, and a control unit configured to control the image forming unit to form adjustment images of the plurality of colors on the intermediate transfer member. And a control unit configured to perform correction processing of determining a correction value of a formation timing of an image of a first color among the plurality of colors on the photosensitive member based on a detection timing of the adjustment image of each of the plurality of colors by the detection unit, wherein the control unit changes the correction value depending on whether a first mode of forming a first additional image on the intermediate transfer member in addition to a user image is selected when the user image based on a print job is formed on a sheet.SELECTED DRAWING: Figure 5

Various examples provide depth image analysis and correction for stereo image machine learning systems and applications. A depth image anomaly identification stage of a depth image anomaly processor can perform functions to evaluate a depth image in order to identify anomalous segments where the values ​​of pixels predicted by a stereo depth perception model appear anomalous in terms of accuracy compared to other regions of the depth image. A correction stage adjusts the depth image based on the identified anomalous segments using one or more correction techniques that can compute estimates or predictions for depth values ​​within the identified anomalous segments. The correction can be based on detected structural characteristics within the spatial volume corresponding to the identified anomalous segments and / or on characteristics of local phenomena (e.g.,lighting, reflections, glare, etc.) are based on factors that have been identified as causing inaccuracies in depth values.

Techniques for filtering iono correction data for global navigation satellite system (GNSS) positioning are provided which involve determining a threshold, or mask, for iono correction filtering based on a statistical analysis of variance data included in iono correction data and resulting residual information determined using the iono correction data. The mask can subsequently be used as a threshold to filter iono correction data based on its variance data. In some examples, a server can determine the mask based on crowdsourced information received from multiple GNSS receivers. In other examples, a GNSS receiver may determine the mask based on obtained iono correction data and GNSS measurements it makes itself. When applying the mask to filter incoming iono correction data. When incoming iono correction data is filtered, a GNSS device may use alternative iono correction techniques to perform iono correction, in some embodiments.

This invention discloses a method and system for calculating industrial time-series data with instantaneous high-frequency characteristics, belonging to the field of real-time computing for power system dispatch automation. The method employs a cache-based out-of-order data correction technique, a streaming-based dynamic delay calculation method, and a reentrant calculation window verification method to adaptively optimize instantaneous high-frequency time-series data. This achieves high-precision, high-frequency, and high-performance industrial time-series data calculation, effectively improving the power grid's operation monitoring level and ensuring its operational safety. This invention is particularly applicable to high-frequency data calculation and analysis of key equipment such as IGBTs and fault recording devices in flexible DC substations, improving the accuracy and real-time performance of power system fault analysis and diagnosis.

The present application relates to the technical field of image pre-training, and particularly relates to a training method and system of an image pre-training model and a storage medium. The method comprises the following steps: collecting original training images, performing high-dimensional feature mapping and pyramid transformation to generate multi-resolution feature bodies, determining the texture definition of the images based on the feature bodies, screening out defective training images and qualified training images, for the defective training images, correcting them into defective correction training images by using a trace correction technology, and constructing positive and negative contrast images to train a defective image pre-training model, at the same time, performing weak disturbance transformation on the qualified training images to generate positive example pairs before and after disturbance to train a qualified image pre-training model, integrating the two pre-training models into a cooperative sample stream, and obtaining a high-performance integrated image pre-training model through integrated pre-training. The present application realizes image quality grading and difference modeling, improves the defect recognition precision, and enhances the model generalization ability.

The invention discloses a reagent card quantitative analysis system and method based on multi-task deep learning, and belongs to the technical field of point-of-care testing (POCT). The analysis system comprises an image acquisition module, a key point detection and image correction module, a color development area extraction module and a multi-task deep learning prediction module. The analysis method comprises the steps of obtaining an original image of a reagent card to be tested, performing standardization processing on the image through a key point detection and image geometric correction technology, further extracting a sub-image of a color development area, finally inputting the sub-image into a fully trained multi-task deep learning model, and outputting a target concentration value. The problems of insufficient accuracy, limited application and the like in reagent card quantitative analysis in the prior art are solved, the influence of background interference and shooting angle difference on a prediction result is remarkably weakened, and robust and accurate quantitative analysis of the concentration of a reagent card target object is realized under a conventional shooting condition; and the generalization capability and the practicability of the intelligent interpretation system are obviously improved.

In various examples, depth image analysis and correction for stereo image machine learning systems and applications are provided. A depth image anomaly identification stage of a depth image anomaly processor may perform functions for evaluating a depth image to identify anomalous segments where the values of pixels predicted by a stereo depth perception model appear anomalous with respect to accuracy in comparison with other regions of the depth image. A correction stage adjusts the depth image based on the identified anomalous segments using one or more correction techniques that may compute estimates or predictions for depth values within identified anomalous segments. Correction may be based on detected structural characteristics within the volume of space corresponding to the identified anomalous segments, and / or based on characteristics of local phenomena (e.g., lighting, reflections, glare, etc.) identified as potentially causing the inaccuracies in depth values.