66 results about "Subjective perception" patented technology

The invention discloses a college dormitory noise multi-dimensional evaluation method based on psychoacoustic and sound field simulation, and belongs to the field of building environment and noise control. The objective of the invention is to solve the problem that an existing dormitory noise evaluation method is single in index and neglects subjective perception and spatial distribution heterogeneity. The method comprises the following steps: acquiring physical data and original audio of dormitory noise through multi-point synchronous acquisition; calculating loudness, sharpness, roughness, fluctuation intensity and comprehensive psychoacoustic annoyance (PA) by using a psychoacoustic model, and scientifically quantifying subjective interference of noise; meanwhile, sound field simulation is carried out based on the accurately established three-dimensional dormitory model, a sound pressure level distribution cloud picture is generated, and a standing wave phenomenon and a sound energy accumulation area are visually revealed; and finally, generating a targeted noise reduction optimization strategy by integrating subjective and objective and spatial analysis results. According to the method, full-chain diagnosis of physical characteristics-subjective perception-spatial distribution of dormitory noise is realized, and a scientific basis is provided for accurate and efficient noise treatment.

The invention discloses a street space pleasure evaluation and optimization method based on multi-source data. The method comprises the following steps: data acquisition: acquiring street scene images, three-dimensional building data and POI data in a research area; subjective perception data acquisition: acquiring a subjective perception score of a user for street pleasure by using a street view image and an online data collection platform; objective index extraction: extracting objective indexes such as physical characteristics, interface characteristics, urban functions and macroscopic forms of streets from the multi-source data; correlation analysis: carrying out correlation analysis on objective indexes and subjective perception scores, and determining key factors influencing street pleasure; establishing an evaluation model: establishing a street space pleasure evaluation model based on the key factors; and optimization strategy making: proposing a targeted street design optimization strategy according to an evaluation result. According to the method, multi-source data and individual perception are comprehensively considered, the street space pleasure can be evaluated more accurately, and a scientific basis is provided for street design and planning.

Aircraft high-load landing event detection, classification and maintenance guidance methods relate to the technical field of aircraft high-load landing event detection. The aircraft high-load landing event detection method collects complete and accurate landing data online during an aircraft landing process and performs an analysis and calculation to determine whether a high-load landing event occurred and determines the type of the high-load landing event. The aircraft high-load landing event detection method removes the high-load landing event determination from the pilot's subjective perception and does not need to wait for decoding of quick access recorder (QAR) data, greatly improving the accuracy and timeliness of high-load landing event detection. In addition, by analyzing and estimating structural loads of the aircraft, the aircraft high-load landing event detection method provides targeted maintenance recommendations for possible aircraft structural damage caused by the high-load landing event, and forms a corresponding report.

The invention discloses a lighting environment evaluation system for simulating an underground working space, and relates to the technical field of lighting environments. Comprising an immersive virtual reality environment experience system which is used for experiencing different space illumination scenes by people in an immersive manner; a human body physiological index acquisition system; the human body subjective perception acquisition system is used for acquiring subjective feelings of personnel through questionnaires preset in a virtual environment; the task performance system is determined by the task collection time length of the visual task preset in the virtual environment and the answer condition, and the work efficiency performance is evaluated through the inverse efficiency score; and the comprehensive data processing system is used for receiving, sorting and analyzing the data collected by each system. According to the method, the limitation of traditional single information feedback and qualitative method evaluation is broken through, diachronic and instantaneous perception dynamic changes are considered, a quantitative evaluation system integrating subjective perception, objective physiological indexes and working efficiency performance is established based on multi-source information feedback, and the method can be applied to long-term closed space place illumination environment evaluation.

The invention discloses an urban park perception value evaluation method based on multi-modal data fusion, and the method comprises the steps: extracting a multi-dimensional perception tag and an emotion intensity score from park social media text comment data through a pre-trained language model, and carrying out the aggregation of the multi-dimensional perception tag and the emotion intensity score, and generating a subjective perception result; performing element identification on the image comment data of the park social media by using the three models to obtain different scene element coverage rates, character / facility counts and language representations of visual elements; constructing a plurality of objective environment indexes to describe different environment states, extracting variable information from three model output results, POI data, remote sensing land class proportion and road network information, and constructing mapping with the corresponding objective environment indexes to quantify each objective environment index; and aligning and outputting the subjective perception result and the objective environment index in the park and period dimensions. According to the method, automatic quantitative evaluation of subjective and objective characteristics of urban parks can be realized on the national scale, and standardized technical support is provided for urban renewal and ecological management.

The invention discloses an urban high-intensity district security assessment method based on multi-source space element coupling, and relates to the technical field of environment assessment, and the method comprises the steps: selecting a high-intensity district of a research city, and obtaining a plurality of observation points; generating a street view panorama of the position of each observation point; for the streetscape panorama of each observation point, space elements are extracted from each streetscape panorama based on image semantic recognition to obtain objective perception indexes, and subjective perception indexes of sight lines of different participating individuals facing different space elements are obtained based on a sight line capture technology; and coupling the objective perception index and the subjective perception index obtained at each observation point based on a multiple linear regression equation to obtain a security evaluation value. According to the method, the physiological basis of subjective psychological security is directly quantified by acquiring the physiological data of the participants facing the spatial elements, objective spatial features and subjective physiological reactions are coupled, and the complex perception of people on the spatial security is reflected more truly.

The invention discloses an earphone defect detection method and device based on voiceprint feature analysis and a storage medium, and relates to the technical field of electroacoustic quality control. According to the method, human ear hearing characteristics are simulated, Mel-cepstrum voiceprint characteristics are extracted from sound response signals, an adaptive weight mechanism based on an equal-loudness curve is introduced, and a voiceprint abnormal deviation index model conforming to human ear subjective perception is constructed; in order to solve the problem that tiny abnormal noise is difficult to recognize, high-order statistics such as kurtosis and skewness are adopted for feature fusion enhancement, and a support vector machine is combined to achieve accurate capture of transient impulse noise. According to the invention, various defect types such as voice coil friction, imbalance of balance degree, diaphragm damage and the like can be fully automatically distinguished, the problems that a traditional test means is disjointed with subjective hearing sense and the omission ratio of hidden defects is high are effectively solved, and the quality inspection efficiency and accuracy of earphone production lines are remarkably improved.

This invention relates to the field of big data analytics, specifically to a method and system for intelligent analysis and assessment of risk perception bias among residents in post-disaster reconstruction areas. The method involves fitting risk indicators using multi-source data and a collaborative model, and calculating risk assessment values ​​based on the fitting results. It obtains basic information data, subjective perception data, and resident behavior data through structured questionnaires. Initial correction coefficients are matched to the subjective perception data based on the basic information data, and error analysis is performed using resident behavior data to determine whether dynamic compensation of the initial correction coefficients is necessary. This significantly improves the accuracy of the final obtained true subjective perception data. By assessing residents' risk perception bias from two perspectives—true subjective perception data and risk assessment values—the method ensures the accuracy and comprehensiveness of the final results, achieving intelligent analysis and accurate assessment of risk perception bias among residents in post-disaster reconstruction areas.

The invention relates to the technical field of physiological index data processing, in particular to a user feedback driven physiological index adaptive health assessment method and device. The method comprises the following steps: acquiring a BCG signal of a user based on a non-contact sensor, and acquiring index monitoring data of a plurality of indexes based on the BCG signal; the user inputs a user feedback text representing the abnormal state of the body, matching is conducted on the basis of the user feedback text and the disease words in the lexicon, and if the disease words are matched, indexes corresponding to the disease words serve as final monitoring indexes; if the disease word cannot be matched, screening out an initial monitoring index based on the user feedback text, and determining a final monitoring index based on the initial monitoring index; and obtaining daily index monitoring data based on the final monitoring index. In this way, mapping from coarse-grained subjective perception to refined objective indexes can be realized, and monitoring blind areas and misjudgment risks are remarkably reduced while the early-stage anomaly detection rate is increased.

The application discloses a kind of urban park perception value evaluation methods based on multi-modal data fusion, utilize pre-trained language model to park social media text comment data extraction multidimensional perception label and sentiment intensity score, and subjective perception result is aggregated and generated;Park social media image comment data is identified using three kinds of models, obtain different scene element coverage, figure / facility count, and language representation of visual elements;A plurality of objective environment indexes are constructed to describe different environmental conditions, variable information is extracted from the output results of the three models, POI data, remote sensing land class proportion and road network information, and a corresponding objective environment index is constructed to map to quantify each objective environment index;Subjective perception result and objective environment index are aligned in park and period dimension and output.The present application can realize the automatic quantification evaluation of subjective and objective characteristics of urban park at national scale, and provide standardized technical support for urban renewal and ecological management.

The present application belongs to the field of X-ray image quality assessment, and specifically discloses a color migration driven X-ray enhanced image quality assessment method and system. Through this application, the idea of bidirectional mapping is proposed, and two enhanced images are obtained by the two methods of "enhancement first and then migration" and "migration first and then enhancement". The accuracy of the assessment is guaranteed by the complementarity of the two enhanced images; this application simulates the visual perception of the human eye based on the Retinex theory, decomposes the image into reflection components and illumination components, and simulates the visual perception mechanism of the human eye to the image by performing comprehensive matching calculation, reflection component evaluation, and illumination component evaluation on the reflection components and illumination components of the original image and the enhanced image, so that the evaluation results can be closer to the subjective perception of human beings to image quality. Therefore, this application can quantitatively evaluate the quality of X-ray enhanced images in actual production scenarios without reference images or high-quality reference images, quantitatively evaluate the effects of various image enhancement algorithms, and provide technical support for selecting more suitable image enhancement algorithms.

The invention relates to a video restoration method and device based on bullet screen feedback, equipment and a medium, and the method comprises the steps: collecting bullet screen data in a video playing process, and recognizing feedback data used for feeding back a video quality problem from the bullet screen data, the feedback data comprising a bullet screen text and bullet screen time; determining a problem type and a problem severity degree of a video quality problem according to the bullet screen text, and determining a problem region of the video quality problem according to the bullet screen text and the bullet screen time; and determining a repair strategy according to the question type and the question severity, and performing video repair on the question region according to the repair strategy. Through a bullet screen semantic recognition mechanism, subjective feedback information of a user on image quality in a video watching process is converted into quantifiable quality problem description, information mapping from subjective perception to objective restoration is realized, and the problem that faults exist between subjective quality feedback of the user and an objective video restoration technology during video restoration is solved.

The invention relates to an image compression method and system based on large and small model collaborative driving, and the method comprises the steps: carrying out the preprocessing of an input image, extracting the image features of each image block of the input image, and carrying out the quantification; side information of the image features is extracted, quantized and compressed into a side information code stream; decoding the side information code stream, and performing feature transformation on the quantized side information to obtain super-prior information; inputting the quantized image features and the hyper-prior information into an entropy model to obtain probability distribution parameters of the quantized image features; compressing the quantized image features into a main code stream, and predicting according to probability distribution parameters to obtain the size of the main code stream; and decoding the main code stream according to the size of the main code stream to obtain reconstructed quantized image features, and realizing multi-target output through a main decoder. Compared with the prior art, the objective signal fidelity of the decoded image in a high code rate interval, the subjective perceptibility of the decoded image in a low code rate interval and the analysis performance of the compressed image in a machine vision scene are remarkably improved.

The invention discloses a Mini-LED backlight display halo perception boundary determination method and system, and aims to solve the problem that a halo boundary in a high dynamic contrast display scene is difficult to objectively define. The method comprises the following steps: acquiring brightness distribution of a display area and a surrounding dark area in a dark environment; guiding an observer to determine a subjective halo boundary position under a standard observation condition; mapping the position to objective brightness data to extract a boundary brightness threshold value; and establishing a sensing boundary model based on multiple groups of peak brightness and boundary thresholds, wherein the sensing boundary model is used for stably determining a halation region which can be sensed by human eyes under different brightness, partition and dimming strategies. According to the method, the perception boundary is used for replacing a fixed absolute threshold value, evaluation consistency is remarkably improved, closed-loop association of subjective perception and objective data is achieved, and reproducible and computable standardized criteria are provided for halo evaluation, algorithm optimization and production line quality control.

The invention discloses a perception image compression model evaluation method based on multi-index fusion, and belongs to the technical field of digital image compression. In order to solve the problem that an existing image quality evaluation method is difficult to comprehensively reflect subjective perception of human eyes, after multiple evaluation indexes are subjected to normalization processing, adaptive fusion is carried out through a three-layer full-connection neural network, and a comprehensive score is output based on a weighted summation mode. According to the method, the image compression quality can be measured more comprehensively and accurately, and the consistency of the model and human eye perception is improved.

The present invention discloses a method, system, computer device and medium for measuring the spatial quality of a living street. The method includes: obtaining street view image data of a target area; establishing a street view image database according to the street view image data, and scoring the street view images through a random forest machine learning model to realize the subjective perception of the street view images; obtaining multiple environmental evaluation indicators of the street through visual image semantic segmentation based on a deep learning fully convolutional network and the K-means clustering algorithm, and conducting an objective environmental evaluation of the street view images; assigning weights to the results of the subjective perception and objective environmental evaluation of the street view images according to the analytic hierarchy process, and calculating the measurement result of the comprehensive evaluation of the street. The present invention can accurately measure the spatial quality of urban living streets, has the advantages of high efficiency and easy popularization and application, and can be widely applied to the field of survey and measurement of the spatial quality of urban planning living streets.

The application discloses a kind of based on modular design's text video quality evaluation method and system, belong to computer vision technical field.The method includes: extracting time sequence, space and the multi-dimensional feature of graphic-text matching degree from original text video;Initial quality score of video is generated using multi-modal base model;Multi-dimensional feature and initial score are fused to generate prediction label;Through feature mapping block generation weight and bias coefficient, initial score is adaptively corrected to obtain final quality score;Using minimum batch learning strategy, combine prediction label dataset with real label dataset, to train quality evaluation model in a supervised learning manner.The application realizes the effective fusion of multi-dimensional quality characteristics through modular design, significantly reduces the dependence of the model on artificial annotation data, improves the consistency of evaluation results and human subjective perception, and provides an efficient and reliable solution for text video quality evaluation.

The invention provides an image quality evaluation method and device and a medium, and belongs to the technical field of video image processing, and the method comprises the steps: obtaining a to-be-evaluated image; dividing the to-be-evaluated image into a plurality of areas; determining each evaluation index of the plurality of areas according to a preset weighting rule to obtain a plurality of evaluation information; and fusing the evaluation information to obtain a quality evaluation result of the to-be-evaluated image. According to the method, the image is subjected to region division, and multi-level and multi-dimensional analysis and quantification are carried out, so that the final quality evaluation result can more accurately reflect the perception quality of human eyes on the image, and the problem of disjunction with subjective perception caused by global statistics or average calculation in a traditional quality evaluation method is solved; and the subjective consistency and the evaluation efficiency of the image quality evaluation result are improved.

The invention discloses a naked eye 3D display system subjective feeling crosstalk measurement method based on image features, and the method comprises the steps: firstly constructing a score crosstalk test image library and a feature score test image library, designing a subjective feeling score table, obtaining a subjective score watched by human eyes, and building a function relation between the subjective score and an image crosstalk value through function fitting; image feature values are extracted through camera shooting, a subjective score prediction model is trained in combination with subjective scores obtained through calculation, and finally subjective feeling crosstalk prediction based on the image feature values is achieved. The method overcomes the defect that the prior art only depends on objective parameter measurement and cannot reflect the subjective feeling of a viewer, can quantitatively measure the subjective feeling crosstalk of a specific image on a specific device, and has high precision (fitting precision 97.8% and relevancy 97.37%) and high efficiency (measurement precision 94.6%). And reliable technical support is provided for optimizing the performance of the naked eye 3D display system.

The present invention discloses a method for evaluating the effects of localized ventilation under clothing on human thermal regulation. The method provides a locally ventilated garment with adjustable and controllable ventilation temperature and speed to evaluate the overall thermal physiological and psychological effects of localized ventilation on the human body. The method can estimate differences in the skin's preference for air temperature and speed when subjected to ventilation and cooling in a thermal environment, as well as differences in the cooling effect and subjective perception of the individual when ventilation and cooling are applied to a specific area of the body. This method comprehensively determines the ventilation location with the lowest energy consumption and the best cooling efficiency, thereby enabling the design of appropriate ventilation locations and parameters for individual ventilation equipment.

The invention provides an image quality evaluation method and device, and relates to the technical field of image processing. The method comprises the steps of obtaining a to-be-evaluated image; performing semantic feature extraction on the to-be-evaluated image by using a Mamba model to obtain multi-scale content features, the multi-scale content features including local distortion detail information and global content information; generating a weight parameter and an offset parameter of a target network by adopting a super network based on the multi-scale content features; and based on the multi-scale content features and the weight parameter and the bias parameter of the target network, adopting a preset image quality prediction target network to evaluate and obtain an image quality result. End-to-end blind image quality evaluation of global dependence modeling, local distortion capture and adaptive quality prediction can be realized, the accuracy of image quality evaluation is improved, and the deviation between an evaluation result and human subjective perception is reduced.

The invention discloses an image color aesthetics evaluation model and an image color aesthetics evaluation method based on a Kolmogorov-Arnold network. According to the method, firstly, multi-level color features of an image are extracted through a Kannform module integrated with a KAN, and modeling of a color relation is enhanced by using the powerful nonlinear capability of the multi-level color features; then, a multi-level feature aggregation module based on KAN space-time attention is adopted, color features of different levels are fused in a self-adaptive mode, and key color areas are highlighted; and finally, mapping the fused features into aesthetic scores by using a KAN feature regression device. The system comprises corresponding function modules. The problems that an existing method is insufficient in color space fine grit perception and prone to being interfered by non-color information, and the nonlinear mapping capacity of a traditional regression device is limited are solved, and the consistency, accuracy and stability of an evaluation result and subjective perception of human eyes are remarkably improved; the method can be widely applied to the fields of smart phone imaging evaluation, social media image screening and the like.

The invention discloses an abdominal tumor angiography magnetic resonance image generation method based on cross semantic perception, and the method comprises the steps: carrying out the refining of a feature graph through introducing a generator based on feature enhancement and multi-scale attention, and enhancing the expression capability of texture details and edge information; in order to enable a discriminator to pay more attention to the spatial and semantic features of the image, the discriminator based on cross semantic perception is designed, and the semantic features of the real angiography image are introduced into the discriminator to serve as additional guide information. Furthermore, the reversibility of conversion is ensured by utilizing cyclic consistency loss, the semantic difference of the image is learned through perception loss, more attention is paid to the visual quality of the image, and the image is closer to the subjective perception of human eyes on the image quality, so that the problem that pixel points between the generated image and the real image are not aligned is solved.

The invention discloses an urban high-intensity district comfort simulation prediction method, which relates to the technical field of environment evaluation, and comprises the following steps: acquiring a street view panorama of each observation point, and extracting a space element of each street view panorama and physiological data of participating individuals corresponding to the space element through an image semantic recognition technology; generating objective perception indexes and subjective perception indexes, constructing a comfort simulation prediction model, establishing a mapping relation between the objective perception indexes and comfort scores and between the subjective perception indexes and the comfort scores, inputting the perception indexes of the observation points into the model, predicting the corresponding comfort scores, and generating a comfort distribution map in the research area through a spatial interpolation algorithm. According to the method, the mapping relation between the objective perception indexes and the subjective perception indexes is established, the perception indexes of the observation points are input into the model for prediction, and the comfort distribution diagram is generated in combination with the spatial interpolation algorithm, so that the comfort distribution condition of the high-intensity area can be intuitively presented.

The invention discloses a video quality evaluation method and device, equipment and a storage medium, and belongs to the technical field of video processing. The method comprises the following steps: acquiring to-be-evaluated video data; extracting saliency semantic information corresponding to the visual attention area in the to-be-evaluated video data, and performing space-time modeling and context analysis on the saliency semantic information to obtain saliency features of the to-be-evaluated video data; extracting multi-scale image features of the to-be-evaluated video data; extracting coding domain features of the to-be-evaluated video data; fusing the saliency features, the multi-scale image features and the coding domain features to obtain fused feature representation; and predicting the fusion feature representation by using a pre-trained video quality evaluation model to obtain a quality evaluation result of the to-be-evaluated video data. According to the method, the video quality can be evaluated by integrating the multi-dimensional features, the problems that various distortion types are difficult to consider and subjective perception of human eyes is difficult to reflect in the prior art are effectively solved, and the video quality evaluation accuracy is improved.

The invention discloses a speech emotion recognition method based on subjective perception deviation knowledge distillation, and the method comprises the following steps: extracting acoustic features of a speech sample to be recognized and subjective perception deviation features corresponding to the speech sample, the acoustic features including spectrum features and self-supervised learning speech representation; inputting the acoustic features and the subjective perception deviation features into a teacher model for fusion to obtain fusion features, and generating a soft label based on the fusion features; inputting the acoustic features into a student model, processing the acoustic features through the feature fusion attention module to obtain student features, and generating a prediction label based on the student features; performing knowledge distillation on the student model by adopting the soft label, and obtaining a trained student model by minimizing the distribution difference between the prediction label and the soft label; and only inputting the acoustic features into the trained student model, and reasoning and outputting an emotion recognition result.

The invention relates to a multi-dimensional evaluation method for optimizing a content distribution strategy, and the method comprises the steps: constructing a comprehensive accelerated distribution effect comprehensive evaluation index system, and analyzing the performance of a whole network within a certain period of time after the distribution strategy takes effect. Quantitative evaluation is carried out from multiple aspects of request hit rate, user time delay, bandwidth consumption, storage occupation, cache updating and the like. The system not only pays attention to the subjective perception of the user in the resource access process, but also quantifies the actual conditions of user experience and system resource utilization through specific performance indexes. Through the multi-dimensional quantitative analysis, the subjective feeling of the user on the service experience can be converted into specific objective data, and a reliable basis is provided for scientific evaluation of the distribution effect.

The present application relates to the technical field of engineering machinery, and discloses a method, device, system and medium for evaluating the amplitude change stability of a hoisting device and the same. The method comprises: determining a plurality of evaluation parameters for characterizing the fluctuation of a measuring point according to amplitude change-related data of the hoisting device at different amplitude change stages under different test conditions, wherein the different amplitude change stages include the starting stage, the steady speed stage and the parking stage during the amplitude change rotation process, and the measuring points include the arm tip and the suspended cargo; and evaluating the amplitude change stability of the hoisting device according to the plurality of evaluation parameters. The present application determines objective evaluation parameters that characterize the fluctuation of the measuring points (arm tip and suspended cargo), promotes the process-based (throughout the starting stage, the steady speed stage and the parking stage) and data-based evaluation of the amplitude change stability, no longer relies on the subjective perception of the evaluator, and improves the accuracy of the equipment amplitude change stability evaluation.

The invention discloses a generative asynchronous voice anonymization method and a related device, and the method comprises the steps: firstly obtaining a voice signal of a speaker, then carrying out the decoupling of the voice signal, obtaining a speaker representation used for recognizing the identity of the speaker, decomposing the speaker representation into D-dimensional feature vectors, and carrying out the recognition of the identity of the speaker through the D-dimensional feature vectors; as the anonymized voice comprises contents in two aspects of machine perception anonymization and human subjective perception anonymization, the feature vector used for identifying machine perception is edited, the identity of a machine recognition speaker can be confused, and finally, the voice signal is reconstructed based on the edited speaker representation, so that the recognition accuracy of the speaker is improved. The generated anonymized voice realizes asynchronous voice anonymization, that is, while human subjective perception is reserved, the identification accuracy of the identity of a machine dialogue person is reduced, so that a good anonymization effect is achieved from the perspective of machine perception, and scene requirements of sound uniqueness, expressive force and specialty of the anonymized voice are met at the same time.

The invention discloses a human-machine cooperation-based village scene image subjective perception evaluation method, system and product, and the method comprises the steps: firstly obtaining a plurality of village scene image data, and obtaining the preprocessed village scene image data through the three rule processing of invalid data elimination, latitude and longitude information extraction and EXIF information deletion; then based on the processed village scene images, randomly pairing each village scene image with other village scene images, and inputting a comparison scoring network based on deep learning to obtain a village scene image comparison sequence with high precision and strong stability; and finally, based on a village scene image comparison sequence, converting the one-group two-group classification result into an absolute score of each village scene image. According to the method, machine intelligence and human cognition are creatively combined, high-efficiency, high-precision and low-cost subjective perception evaluation of mass village scene images is realized, and decision support with objective data support and subjective cognition basis is provided for rural planning.