24 results about "Temporal resolution" patented technology

This application relates to the field of medical image processing technology, and provides a method, apparatus, device, and storage medium for reconstructing ECT images. This allows for more thorough capture of subtle changes in the concentration distribution of radioactive tracers at high temporal resolution, helping to reduce image noise levels and improve image quality. This application obtains a first ECT image sequence; the first ECT image sequence is obtained by scanning with an ECT scanning device; the first ECT image sequence is input into a pre-constructed intermediate frame prediction network to obtain an estimated second ECT image sequence; using the estimated second ECT image sequence as a priori image, a target second ECT image sequence is reconstructed; the estimated second ECT image sequence and the target second ECT image sequence belong to the second ECT image sequence; the temporal resolution of the second ECT image sequence is higher than that of the first ECT image sequence.

A device can retrieve data representing a plurality of activity sequences associated with a plurality of channels. Each activity sequence can include a plurality of activity entries having data values for a plurality of fields. The plurality of activity entries can be associated with respective timestamps. The plurality of activity sequences can have respective temporal resolutions. The device can flatten the data values of the plurality of activity sequences into a single time-ordered activity sequence across the plurality of activity entries, the plurality of fields, and the plurality of channels. The device can generate an activity data embedding using the single time-ordered activity sequence, generate an encoder output based on the activity data embedding and temporal information based on the respective timestamps using an encoder module, input the encoder output into a decoder module, and generate a decoder output based on the encoder output using the decoder module.

This invention discloses a device and method for detecting boundary changes in a video wall splicing mirror, relating to the field of optical inspection technology. The detection device includes a contact sensing structure, a non-contact optical structure, and a processor arranged relative to the video wall splicing mirror body. The detection of boundary changes in the video wall splicing mirror is achieved based on the contact sensing structure and the non-contact optical structure. Furthermore, when using the contact sensing structure, the edge sensor readings are corrected by introducing a mounting arm length parameter, eliminating Abbe errors caused by the misalignment of the mounting reference plane and the optical neutral plane, thus improving the accuracy and reliability of the contact detection. An event sensor is introduced into the non-contact optical structure; this event sensor can typically capture transient events of edge changes with microsecond-level time resolution, making it suitable for real-time detection in dynamic environments. In addition, the contact sensing structure and the non-contact optical structure can serve as backups for each other, improving the reliability of the detection device.

This invention discloses an underwater acoustic positioning sound velocity compensation method based on vertical total time delay random walk, belonging to the field of underwater acoustic navigation and positioning. The method includes: collecting two-way time delay observation data in underwater acoustic positioning; establishing an ocean sound velocity compensation formula; defining the vertical total time delay and establishing a conversion function between ocean sound velocity variation and vertical total time delay; calculating a coarse prior value of the vertical total time delay based on the conversion function, and using a first-order Markov process to calculate the random walk noise of the vertical total time delay; using the two-way time delay observation data, the coarse prior value, and the random walk noise, accurately estimating the vertical total time delay using an extended Kalman filter, and then substituting it into the conversion function to obtain the ocean sound velocity variation, thus achieving sound velocity compensation. This invention eliminates the need for additional sound velocity measurement equipment, enables real-time online compensation of ocean sound velocity variation errors, improves underwater acoustic positioning efficiency, and enhances the temporal resolution of ocean sound velocity variation detection.

This invention belongs to the field of computer vision and intelligent environmental perception technology, specifically relating to a method for anomaly detection and intensity estimation of sandstorms based on event cameras. It includes constructing and training an estimation model based on a multi-stream regression framework, and using the trained estimation model to predict sandstorm concentration. The estimation model includes an encoding module, a temporal distillation module, a cross-channel interaction module, and a regression prediction module. The encoding module includes three parallel color spectral encoders for red, blue, and green. This invention effectively overcomes the technical limitations of traditional air quality prediction methods based on RGB images, such as insufficient temporal resolution, limited dynamic information expression capabilities, and insufficient utilization of information from a single data source. It achieves high-precision estimation of air particulate matter concentration and maintains good robustness and adaptability even under complex environmental conditions.

This invention discloses a rapid detection method and system for antibiotic residues in vegetables based on chlorophyll fluorescence imaging, belonging to the field of non-destructive testing technology for agricultural product quality and safety. The invention applies saturated pulsed light to dark-adapted vegetable leaves and acquires multi-temporal resolution fluorescence imaging sequences at a logarithmic scale within the transient time window from phase J to phase I of the rapid chlorophyll fluorescence induction kinetics. From these sequences, a temporal feature tensor composed of transient inflection point time shifts and a spatial feature tensor composed of leaf vein-mesophyll boundary heterogeneity textures are extracted. These two tensors are then fused using a Tucker core tensor cross-external product to obtain an antibiotic type fingerprint tensor. The antibiotic type and confidence level are output through CNN classification. Finally, a category-conditional gradient boosting regression is used to output concentration prediction values, and a reverse closed-loop adjustment is applied to adjust the sampling time window and region of interest. This invention achieves integrated rapid detection of antibiotic residues at the level of tens of micrograms per kilogram in vegetables, combining type identification and concentration quantification.

This invention relates to a continuous three-dimensional particle field reconstruction method based on single-light-field imaging using EM deconvolution, belonging to the field of optical imaging technology. This method employs a light field camera to capture light field images of a discretized three-dimensional flow field, acquiring the light intensity information of scattered light emitted by particles on each pixel of a CCD detector. Based on the light intensity information, a weight matrix for each voxel is calculated, and the entire weight matrix is ​​loaded only once. The nth frame of the light field image is loaded, and the non-zero pixels in the nth frame are identified. The non-zero pixel sequence formed by the scattered light from tracer particles is extracted. An EM deconvolution algorithm is used to iteratively calculate the non-zero pixel sequence, updating the intensity of each voxel, thereby reconstructing the three-dimensional particle field of a single frame. The above steps are repeated to complete the reconstruction of the three-dimensional particle field from multiple frames of high temporal resolution light field images, resulting in higher reconstruction accuracy and consistency, and less time consumption.

A method for the spatially-resolved probing of bio logical tissue (102) comprises the steps of emitting, by means of at least one light source (106), a series of light pulses into the tissue and of measuring, by means of a plurality of light detectors (108), a plurality of time-resolved responses to the light pulses scattered from the tissue. The measurement is carried out with a temporal resolution better than 20 ps. A plurality of first responses is in response to light pulses at a first illumination band and is measured at a plurality of first detection bands. The first detection bands differ from each other and from the first illumination band in order to detect inelastic scattering. A plurality of second responses is in response to light pulses at a second illumination band and is measured at a second detection band. The second detection band overlaps with the second illumination band in order to detect elastic scatting. Time of flight analysis of both responses allows to e.g. use elastic scattering for locating structures (S1, S2, S3) in the tissue (102) and for assigning them to the inelastic scattering data.

This invention discloses an ultra-high spatiotemporal resolution single-shot measurement system based on warm-dense gold, belonging to the field of pump-probe technology. It includes a femtosecond laser module, a femtosecond pulse compression module, a femtosecond pulse shaping module, a 400nm few-period femtosecond pulse module, a sample module, a probe light module, and an imaging system module. The femtosecond laser module provides a femtosecond laser beam, which is compressed by the femtosecond pulse compression module to generate a few-period femtosecond pulse. After optimization by the femtosecond pulse shaping module, the pulse is split into two beams. One beam is used to generate an ultraviolet-band few-period femtosecond pulse through the 400nm few-period femtosecond pulse module, serving as the pump light. The other beam is used to generate an 800nm ​​few-period femtosecond pulse through the probe light module, serving as the probe light. The sample to be measured is placed inside the sample module, and the pump light and probe light act on the sample module simultaneously. Imaging is achieved through the imaging system module. This invention solves the problem that due to low temporal resolution, the Auger time of electrons in metals is on the order of 10 femtoseconds, making it impossible to effectively detect the initial processes of the formation of warm-dense materials.

This invention discloses an on-orbit intelligent processing method for spaceborne images based on brain-like computing, belonging to the field of on-orbit intelligent processing of spaceborne images. This invention utilizes a spiking neural network to simulate the structure of the human brain: including a feature extraction layer, a pulse coding layer, an STDP learning layer, a lateral inhibition layer, and a decision output layer; and improves model accuracy through on-orbit updates and federated learning. This invention reduces computational energy consumption and improves efficiency. Simultaneously, this invention leverages the synaptic plasticity of neurons to construct a SNN with excellent spatial and temporal resolution.

This disclosure belongs to the field of laser-induced breakdown spectroscopy technology, specifically relating to a laser-induced breakdown spectral correction method and system based on energy level radiation attenuation. The method includes: acquiring the temporal resolution spectrum of a calibration sample; determining a correction spectral line of the calibration sample based on the acquired temporal resolution spectrum; calculating the energy level radiation attenuation coefficient of the selected correction spectral line based on its temporal resolution spectral line intensity; and correcting the spectral line intensity of the acquired temporal resolution spectrum of the calibration sample based on the obtained energy level radiation attenuation coefficient of the calibration sample's correction spectral line, thereby completing the laser-induced breakdown spectral correction. This embodiment calculates the energy level radiation attenuation rate, correcting the repeatability problems caused by the uncertainty of the energy level radiation attenuation rate within the laser-induced plasma and the uncertainty of radiation attenuation within the integration time, thus improving measurement accuracy.

A kind of optical fiber pulse laser radar system for measuring atmospheric water vapor concentration profile, comprising multi-wavelength optical fiber laser emission module and data acquisition and processing module, three different wavelength pulses are generated by using first, second online seed laser and offline seed laser in multi-wavelength optical fiber laser emission module, two online wavelengths are respectively locked to water vapor absorption peak center by seed light frequency stabilization module, after being alternately output by optical switch, energy amplification is carried out by distributed Bragg reflection type fiber amplification module and emitted to atmosphere, first online wavelength and offline wavelength are combined to detect high layer water vapor concentration in troposphere by data acquisition and processing module, second online wavelength and offline wavelength are combined to detect low layer water vapor concentration in troposphere, and water vapor concentration profile is obtained by inversion.The present application adopts double-wavelength pair adaptive layered detection strategy, combines all-fiber DBR resonant cavity structure, and realizes high-precision, high-spatial and temporal resolution, all-day water vapor concentration profile measurement.

The application discloses a kind of carbon dioxide partial pressure remote sensing monitoring method, system and equipment based on random forest, comprising: obtaining the measured carbon dioxide partial pressure data of target sea area multi-year period, and multi-source remote sensing data and reanalysis data covering corresponding period;According to the space-time information of measured carbon dioxide partial pressure data, the corresponding environmental parameters are matched to construct modeling dataset;Feature variable is selected from modeling dataset, and carbon dioxide partial pressure inversion model is constructed based on random forest algorithm;The accuracy of the optimized model is verified using the test set, and sensitivity analysis is carried out to evaluate the stability of the model;The verified carbon dioxide partial pressure inversion model is applied to the time series environmental parameter data of target sea area, and high spatial and temporal resolution monitoring of carbon dioxide partial pressure is realized.The application has the advantages of no need for field observation, compatible with multi-source data, strong universality, etc., and can be effectively applied to large-scale, long time sequence of marine carbon monitoring task.

The application discloses a kind of atmospheric pollutant estimation system and method based on geographic weighted depth forest, it is related to environmental monitoring, atmospheric science and machine learning cross technical field.The application breaks through the shallow application of traditional geographic weighted random forest to geographic weight, first complete multi-source heterogeneous data space-time matching and preprocessing;Geographic weight loss random forest (GLRF) is constructed, generates geographic weight by adaptive kernel function and reconstructs split criterion by embedding loss function in depth, realizes model innovation in combination with adaptive bandwidth and continuous space-time feature coding.Using Monte Carlo resampling to weaken meteorological interference, generate high spatio-temporal resolution meteorological normalized PM2.5 data nationwide;The application solves the problem of insufficient modeling accuracy of non-stationary space at national scale, overcomes the defects of poor adaptation, low fitting and difficult to identify mutation of traditional model, can eliminate meteorological fluctuations, capture human pollution mutation such as heating, and provide support for environmental protection policy evaluation and clean energy transformation.

The present disclosure provides a pollution level area proportion estimation method, device, equipment and medium. The pollution level area proportion estimation method of the present disclosure comprises: obtaining pollution grid point data of a target area according to the latitude and longitude of the target area, and an element in the pollution grid point data representing a pollution value at a corresponding grid latitude and longitude coordinate; generating a plurality of contour line regions using the pollution grid point data of the target area and a plurality of predetermined pollution level thresholds, each contour line region corresponding to a pollution level threshold and the pollution values of points in the contour line region being less than the pollution level threshold; dividing the target area using the plurality of contour line regions to obtain a plurality of polygon regions with different pollution levels, the pollution levels being determined by the plurality of pollution level thresholds; and calculating the area of each polygon region to obtain the pollution level area proportion of the target area. The present disclosure can effectively reduce the calculation complexity, improve the estimation efficiency, and also has high estimation accuracy and spatial-temporal resolution.

The present application provides a kind of sea surface foam thickness remote sensing inversion method and system, for the L-Ka dual-band of sea surface foam coverage, foam thickness is cooperatively inverted, from the multi-band microwave radiation transmission characteristics, utilize the radiation characteristic difference of foam layer under different frequencies, establish the foam brightness temperature prediction model based on microwave band, the model considers the emission and scattering characteristics of the medium in foam layer, the emissivity of different thickness foam layer is calculated using radiation transfer equation.Then, the quantitative relationship between foam thickness and sea surface wind speed is established, by coupling sea surface foam model and wave spectrum model, sea surface foam coverage, thickness inversion is realized.The method and system provided by the present application can break through the limitation of traditional hydrodynamic model, realize large-scale, high spatio-temporal resolution observation of sea surface foam thickness, provide a new observation method for in-depth understanding of sea-air interface dynamics process.

The application provides a kind of based on stationary satellite hourly all-weather ground temperature reconstruction method, comprising the following steps: S1. collect ground temperature data and multi-source characteristic variable auxiliary data and construct sample data set;S2. construct temperature intra-day cycle model dynamic constraint kernel driven model, simultaneously realize spatial downscaling and ideal ground temperature reconstruction;S3. by hybrid neural network driven spatio-temporal fusion method regression and prediction, estimate weather interference and sensor system error;S4. superimpose weather interference and sensor system error on ideal ground temperature, reconstruct all-weather ground temperature.The method of the application organically combines kernel driven and spatio-temporal fusion method, realizes the reconstruction of all-weather ground temperature with high spatio-temporal resolution based on stationary satellite FY-4A ground temperature product.The method has good stability and interpretability, and the reconstruction result has high precision.

The present application relates to renewable energy assessment and weather forecasting technical field, especially to a kind of wind and light resource fine estimation method based on numerical simulation and observation constraint. Global climate model driving field set is constructed, and the optimal GCM combination is screened out;Regional climate model framework is constructed;High spatio-temporal resolution simulated wind speed and solar radiation data are obtained;Generate kilometer level, hourly wind and light resource data set of history and future. The present application provides a kind of wind and light resource fine estimation method based on numerical simulation and observation constraint, by introducing high resolution, multi-source fusion ground surface wind speed and solar radiation long sequence historical observation data, using quantile mapping method to carry out systematic deviation correction to simulation result, realize statistical downscaling processing under the observation data constraint, finally obtain the wind resource data with 5 kilometers horizontal resolution, so as to significantly improve the high spatio-temporal resolution information capture ability to future wind resource change.

Providing an X-ray measurement with a reduction in the measure of scattered photons is significantly advantageous over measurements with a usual contribution of scattered photons. Using a temporal point spread function (TPSF) of the detected photons, for each source-detector location, to discriminate the scattered photons from the ballistic photons is used to significantly relax the temporal resolution requirement at the time-sensitive X-ray detector of the X-ray imager when compared to the low temporal resolution required when the discrimination is carried out on a photon-by-photon basis. Using the TPSF dataset provides better estimates of the measure of ballistic photons with a reduction in the measure of scattered photons which are also used to generate X-ray images with an improvement in CNR.

The present application relates to the field of hydrological remote sensing and geographic information technology, and more particularly to a water body and water level cooperative extraction method and system. The method comprises the following steps: collecting multi-source remote sensing data of a target area within a preset time period; extracting water body information of optical image data in the multi-source remote sensing data to generate a water surface mask, and quantitatively extracting water body morphological characteristic parameters based on the water surface mask; extracting observation data within the spatio-temporal range of the water surface mask in the spaceborne radar altimeter planar water level data that meets the water body morphological characteristic parameters to construct an initial planar water level field; performing spatio-temporal matching and spatial correction on the spaceborne laser radar point elevation data in the multi-source remote sensing data and the initial planar water level field; and performing spatio-temporal fusion according to the spatially corrected planar water level field and the spatio-temporal change information of the water surface mask. The present application can break through the limitations of a single data source in terms of spatio-temporal resolution and continuous monitoring capability, while improving the water level inversion accuracy and reliability.

The invention relates to a motion determination device for determining a motion of an object. The motion determination device comprises a magnetic resonance (MR) information providing unit (2, 5) for providing MR images of the object (6) and for providing non-image MR data of the object, the non-image MR data having been acquired at different acquisition times, and a motion determination unit (9) for determining a motion field describing the motion of the object (6) from the provided non-image MR data acquired at the different acquisition times and from the provided MR images. Since the non-image MR data, which are preferably k-space data, are directly used for determining the motion field, i.e. without intermediate reconstruction of MR images based on the non-image MR data, the motion field can be determined with a very high temporal resolution.

This application discloses a high temporal resolution magnetic resonance temperature imaging method and apparatus, belonging to the field of magnetic resonance temperature imaging technology. The high temporal resolution magnetic resonance temperature imaging method includes: scanning the region to be diagnosed using a radial sequence based on magnetic resonance coils to acquire k-space data corresponding to the region; grouping the k-space data, the spokes of the radial sequence, and the weights of the radial sequence based on time frames to acquire at least two groups of grouped data; reconstructing the at least two groups of grouped data based on the sensitivity map of the magnetic resonance coils to acquire multiple target time frame images; ensuring that the multiple target time frame images are free of undersampling artifacts; and acquiring a target temperature change image based on the temperature difference between any two adjacent target time frame images. This high temporal resolution magnetic resonance temperature imaging method can acquire the continuously changing temperature process of the region to be diagnosed, improving the temporal resolution of the temperature change process.

The application discloses a crop canopy temperature spatio-temporal estimation method and system based on deep learning, and relates to the field of agricultural information technology.The method comprises the following steps: acquiring multi-time unmanned aerial vehicle visible light and thermal infrared images, preprocessing and calculating vegetation indexes; collecting hourly meteorological data and screening through integrated empirical mode decomposition; constructing and aligning a time series matrix on selected pixels.An integrated model composed of time series convolution, long short-term memory and sparse attention is established, and training, evaluation and prediction are completed in cooperation with double masking and sliding windows; the masking is closed to realize extrapolation of missing and future time; the spatio-temporal continuous canopy temperature field is generated by traversing each pixel.By fusing high-resolution thermal infrared, vegetation index and meteorological multi-source information, the meteorological changes are described in multiple scales, the single variable dominance is suppressed, and the stability and robustness under abnormal climate are improved; the day and night dynamics can be represented, the estimation accuracy and spatio-temporal resolution are significantly improved, and the demand of microclimate monitoring of precision agriculture is met.