37results about How to "No loss of detection accuracy" patented technology

Methods and apparatuses for quality control and detecting errors related to the manufacturing and production of more accurate patterns and resultant devices are provided. The patterns or devices may include patterns used in display applications such as TFT-LCD, OLED, SED, PDP, FED, LTPS-LCD and similar display technologies using at least partially cyclical patterns.

The invention discloses a method and equipment for simultaneously inspecting a plurality of liquid substances by using dual-energy computed tomography (CT). The method comprises the following steps of: performing dual-energy CT scanning on inspected liquid substances at a plurality of positions to acquire dual-energy CT protection data; rotating CT images of the inspected liquid substances after performing the dual-energy CT scanning at each position so as to align the images formed by multiple times of scanning operation; performing CT reconstruction according to the projection data to acquire the CT images for representing physical attribute values of the inspected liquid substances; extracting the physical attribute values of the inspected liquid substances according to the CT images; and judging whether the inspected liquid substances are suspicious based on the physical attribute values and reference physical attribute values of the liquid substances. By the method, the liquid substances can be inspected rapidly.

The invention discloses a method for detecting wireless sensor network sparse events based on compressed sensing and the game theory, which belongs to the field of wireless communication and aims to solve the problem that excessively intensive sensor nodes randomly released in the wireless sensor network probably cause communication interface but sparse sensor nodes probably cause detection leak.The method disclosed by the invention comprises the following steps: (I) dividing M sensor nodes randomly released in the network system into a layers according to the thought of the game theory; (II) determining to activate one or more layers of sensor nodes according to the number (K) of the current events; (III) receiving a data vector y by a data terminal of the network system, and obtaining a measurement matrix [phi]P*N according to the detection process; and (IV) obtaining the specific distribution vector E of K happening events in N event sources by use of a greedy sparse event detection algorithm.

The invention relates to a strip steel surface defect detection method based on deep learning. According to the method, the local information of the surface of the strip steel is extracted through a defect judgment and defect classification double-flow network model. The comprehensive analysis is conducted in combination with a scale pyramid, a similar heat map is obtained. Finally, the types andpositions of defects are obtained at the same time. The defect judgment and defect classification double-flow network model comprises defect judgment branches and defect classification branches. Compared with the prior art, the method has the advantages of being small in calculation amount, high in calculation efficiency, high in robustness, low in labeling cost, high in precision, low in equipment cost and the like.

The invention discloses a low-voltage reset method used in a microcontroller. A low-voltage reset circuit of the low-voltage reset method comprises a low-voltage detection circuit which is controlled by a sleep signal of a system, and also comprises an anti-interference management circuit which utilizes a clock signal in a microcontroller circuit for filtering and generates a reset signal, wherein an output signal of the low-voltage detection circuit and the clock signal are input signals of the anti-interference management circuit together. The low-voltage reset method guarantees that the reset circuit has the characteristics of low power consumption, high precision, anti-interference and so on, so that the microcontroller product can be operated in a situation with low power consumption and realize good electrifying property.

The invention discloses a method and equipment for confirming a CT (Computed Tomography) scanning position in a dangerous goods inspection system. The method comprises the following steps of: firstly, through a CT scanning and dual-energy rebuilding method, obtaining one or more layers of CT images containing physical attributes of liquid to be tested; secondly, through an image processing and analyzing method, obtaining a physical attribute value of each liquid to be tested from the CT images; and finally, judging whether the liquid-state object to be tested is a dangerous goods or not according to the physical attribute value. The CT scanning method comprises a regular sectional CT scanning technology and a spiral CT scanning technology; and when the regular sectional CT scanning technology is utilized, a series of specific positions can be set so as to be scanned, a scanning position can be specified by an operator through a DR (Digital Radiography) image, and the position of a liquid part can be confirmed through automatic analysis on the DR image, so that CT scanning is guided.

The invention discloses a method and equipment for carrying out rapid and safe inspection on a liquid article by dual-energy CT (Computed Tomography) imaging. The method comprises the steps of: firstly obtaining a monolayer or multilayer CT image comprising physical attributes of the inspected liquid by virtue of CT scanning and a dual-energy reconstruction method; then obtaining the physical attribute value of each inspected liquid from the CT image by an image processing and analyzing method; and finally judging whether the inspected liquid article is a dangerous article or not according to the physical attribute value, wherein the CT scanning method can be realized by routine tomography CT scanning technique, and can also be realized by spiral CT scanning technique; and when the routine tomography CT scanning technique is used, a series of specific positions can be arranged for scanning, or the scanning positions can be appointed by an operator by virtue of an DR (Digital Radiography) image, or the liquid part position is determined by automatic analysis of the DR image so as to guide CT scanning.

The invention discloses a method and device for carrying out rapid safety check on liquid articles by double-energy computed tomography (CT) imaging. The method comprises the steps of: firstly, obtaining a layer or a plurality of layers of CT images containing the physical attribute of the detected liquids by a CT scanning method and a double-energy reconstruction method; acquiring the physical attribute value of each detected liquid from the CT images by a image processing and analyzing method; and finally, judging whether the detected liquid articles are dangerous articles or not according to the physical attribute value, wherein the CT scanning method comprises the conventional CT scanning technology and also can be realized by spiral CT scanning technology. When the conventional CT scanning technology is used, a series of specific positions can be set to be scanned, the positions to be scanned can be appointed by an operator by means of a digital radiography (DR) image, and the CT can be guided to scan the positions of liquid parts confirmed by the automatic analysis for the DR image.

The invention discloses a laser in-situ detection system for oxygen concentration in an arsenic-bearing gold concentrate roasting furnace. The system mainly comprises a semiconductor laser, a temperature and current controller for driving the semiconductor laser, a signal generator for generating driving signals, an optical probe for receiving and converting laser beams, a sensor for collecting the temperature and pressure inside the roasting furnace, a data acquisition module for receiving and collecting photoelectric, temperature and pressure signals and an upper computer for computing and detecting the oxygen concentration. The system overcomes the background radiation interference in a combustion environment through the steps of background radiation filtering, baseline correction, absorbance Voigt linear fitting, correction computation of oxygen spectral lines, oxygen concentration computation and inversion and the like, and realizes real-time accurate detection of the oxygen concentration in the roasting furnace.

The invention discloses a method and equipment for inspecting a liquid article by dual-energy helical computed tomography (CT). The method comprises the following steps of: emitting high-energy and low-energy X rays by a ray source; detecting and acquiring the high-energy and low-energy X rays penetrating at least one liquid article to be inspected; carrying the liquid article to be inspected to ensure it can rotate around an axis and can be lifted, so that the liquid article to be inspected enters a detection region, and the high-energy and low-energy X rays emitted by the ray source can penetrate the liquid article to be inspected; performing dual-energy helical CT scanning on the liquid article to be inspected to form a group of helical CT images, each of which represents at least one physical attribute value of the liquid article to be inspected; analyzing the group of helical CT images to determine a helical CT image part of the liquid; and judging whether the liquid article is a dangerous article based on the physical attribute values and reference physical attribute values of the liquid article. By the invention, the liquid article can be quickly inspected.

The invention discloses a method and device for checking a liquid article by a dual-energy CT (computed tomography). The method comprises the following steps: carrying out DR (data recording) scanning on the liquid article to obtain a transmission image of the liquid article to be checked; analyzing the pixel values of the transmission image to determine whether the transmission image is laminated or not; carrying out dual-energy CT scanning on the liquid article to be checked at one or more than one positions in each layer to obtain dual-energy CT projection data; carrying out CT rebuilding according to the projection data to obtain a CT image indicating physical attribute values of the liquid article to be checked; extracting the physical attribute values of the liquid article accordingto the CT image; and judging whether the liquid article is counterfeit based on the physical attribute values and the reference physical attribute values of the liquid article. By applying the invention, the liquid article can be rapidly checked.

The invention discloses an online learning method for video target detection, and belongs to the field of machine vision. The method comprises the steps of model pre-training, target detection, tracking correction, label correction, key frame extraction and model iterative updating. The method comprises the steps of firstly, training a current model of a basic version by utilizing an open source or self-annotation data set; pre-detecting the video sequence by using the current model; utilizing an improved KCF tracking algorithm and a k-nearest neighbor algorithm based on a feature space to respectively perform box correction and label correction on a pre-detection result; extracting a video key frame by utilizing a key frame extraction method based on feature space similarity measurement,and removing repeated images; and training the model by utilizing the key frame data and the correction detection result to realize iterative updating of the model. According to the method, detectionand labeling results are corrected through a tracking algorithm and clustering analysis, a target detection model is retrained by utilizing the corrected results, continuous improvement of model performance is realized, and self-adaptation of an application scene is realized.

The invention discloses a method for detecting a liquid article by using a double-energy spiral CT (captive test) and a device. The device comprises a ray source, a detecting and collecting device, a load bearing mechanism, a controller and a computer, wherein the ray source is used for emitting high-energy and low-energy X rays; the detecting and collecting device is used for detecting and collecting the high-energy and low-energy X rays which penetrate through at least one detected liquid article; the load bearing mechanism can bear the detected liquid article to rotate around a shaft and can move up and down so that the detected liquid article enters a detection area, thereby leading the high-energy and low-energy X rays emitted by the ray source to penetrate through the tested liquid article; the controller controls the ray source and the detecting and collecting device to carry out double-energy spiral CT scanning on the detected liquid article so as to form a group of spiral CT images which respectively represent at least one physical attribute value of the detected liquid article; and the computer analyzes the group of spiral CT images so as to determine the spiral CT image part of liquid and judges whether the detected liquid article is suspicious based on the physical attribute value and the reference physical attribute value of the liquid article. The method can quickly detect the liquid article.

The invention discloses a correction method of a spectrograph for detecting the nutrient content of a plant, which comprises the following steps of: performing full scale correction to the spectrograph for detecting the nutrient content of the plant without a detecting sample to obtain a full scale correction coefficient; performing sample correction through a standard detecting sample with an evenly-distributed SPAD value and a fixed value to obtain the practical numerical reading correction coefficient of the spectrograph according to the full scale correction coefficient; and performing practical correction to the practical detecting value of the spectrograph for detecting the nutrient content of the plant with the full scale correction coefficient and the spectrograph practical numerical reading correction coefficient. The correction method can overcome the influence of the elements such as the light intensity of light source, the parameter of measuring environment, the dynamical property of a photoelectric sensor, and the electric quantity of power-supplying cell, and the like to the detecting reliability and the precision of the spectrograph for detecting the nutrient content of the plant, greatly improves the detecting precision and reliability of the spectrograph, and improves the adaptive capacity to environment of the spectrograph, compared with the existing domestic spectrograph.

The invention discloses a laser in-situ detection system for oxygen concentration in an arsenic-bearing gold concentrate roasting furnace. The system mainly comprises a semiconductor laser, a temperature and current controller for driving the semiconductor laser, a signal generator for generating driving signals, an optical probe for receiving and converting laser beams, a sensor for collecting the temperature and pressure inside the roasting furnace, a data acquisition module for receiving and collecting photoelectric, temperature and pressure signals and an upper computer for computing and detecting the oxygen concentration. The system overcomes the background radiation interference in a combustion environment through the steps of background radiation filtering, baseline correction, absorbance Voigt linear fitting, correction computation of oxygen spectral lines, oxygen concentration computation and inversion and the like, and realizes real-time accurate detection of the oxygen concentration in the roasting furnace.

The invention relates to the technical field of silicon-based surface quality detection, in particular to an ultra-fast silicon-based surface quality detection system. The system the following devices: a mode-locked femtosecond pulse light source, a mid-infrared optical filter, a dispersion optical fiber, an erbium-doped fiber amplifier (EDFA), a diffraction grating, a 4f imaging system based on alens, an objective lens, a digital coherent receiver, a high-speed sampling oscilloscope and a computer required for data processing and recovery. The system further comprises a circulator, a coupler, an optical fiber, an optical fiber polarization controller, a collimator, and the like which are needed to be used.

The invention discloses a method and equipment for quickly and safely inspecting liquid articles through dual-energy computerized tomography (CT) imaging. The method comprises the following steps of: obtaining a layer or multiple layers of CT images containing physical attributes of an inspected liquid by CT scanning and dual-energy reconstruction methods; acquiring the physical attributes of each inspected liquid from the CT images by an image processing and analysis method; and finally, comparing obtained physical attribute values with reference physical attribute values of the liquid article to judge whether drugs are hidden in the inspected liquid article. A CT scanning method comprises the conventional CT scanning technology, and can also comprise a spiral CT scanning technology; and when the conventional CT scanning technology is used, a series of specific positions can be set for scanning, the scanning position can also be assigned by an operator by means of a digital radiography (DR) image, and the position of a liquid part can also be determined by automatically analyzing the DR image so as to guide CT scanning.

The invention provides a capacitance detection device (30) capable of shortening the time required for detection without reducing the detection accuracy. The device is provided with: a capacitor arrayhaving a plurality of capacitors connected in parallel and having mutually different capacities, the combined capacity of the capacitor array changing; a detection capacitor connected in series to the capacitor array; a switch control unit; a detection unit that detects an intermediate potential, which is a potential of a capacity divided voltage of the power supply obtained from the combined capacity and the capacity of the detection capacitor; an acquisition unit that acquires, as a first synthesized capacity and a second synthesized capacity, any one of the synthesized capacities in the vicinity where the magnitude relationship between the intermediate potential and the reference potential is inverted; a computation unit that computes estimated composite capacities of the capacitor array on the basis of first and second intermediate potentials, which are intermediate potentials when the composite capacities are the first and second composite capacities, respectively; and a derivation unit that derives the capacity of the detection capacitor as a detection capacity on the basis of the estimated combined capacity.

The invention discloses an instrument identification and reading method based on a lightweight network, and relates to the technical field of instrument measurement, and the method comprises the following steps: obtaining an original image with an instrument; performing instrument target identification and classification on the original image to obtain a classified instrument image; identifying the classified instrument image by adopting a fine-grained classification network combined with mixed attention clipping to obtain range information of the instrument image; based on the measuring range information of the instrument image, obtaining an instrument reading; according to the method, the learning ability of the model for image detail targets is improved through a multi-scale feature fusion means, the operation efficiency of the algorithm is improved through single-scale YOLO calculation, and meanwhile, the detection precision of instrument targets is not reduced; and automatic identification, reading and data storage of the instrument can be realized, tedious manual identification and recording work is omitted for workers, the efficiency of the workers is improved, and meanwhile, the utilization rate of data is improved.

The invention discloses a method and equipment for simultaneously inspecting a plurality of liquid substances by using dual-energy computed tomography (CT). The method comprises the following steps of: performing dual-energy CT scanning on inspected liquid substances at a plurality of positions to acquire dual-energy CT protection data; performing CT reconstruction according to the projection data to acquire the CT images for representing physical attribute values of the inspected liquid substances; rotating the CT images of the inspected liquid substances after performing the dual-energy CT scanning at each position so as to align the images formed by multiple times of scanning operation; extracting the physical attribute values of the inspected liquid substances according to the CT images; and judging whether the inspected liquid substances are dangerous substances based on the physical attribute values. By the method, the liquid substances can be inspected rapidly.

The objective of the present invention is to provide an illuminating device which uses one illuminating light source to supply an amount of light onto an object being detected, to create a detection image which is bright overall and which has no parts in shadow. A light source required to illuminate the object being detected from above and below is shared, and the object being detected is illuminated by the light from the illuminating light source being received by a plurality of reflectors and divided to form upward illuminating light and downward illuminating light. Further, optical paths ofat least some light beams from the illuminating light source are reflected by a refracting mirror and are then caused to be incident on the reflectors. In this way, the number of illuminating light sources can be reduced without causing a reduction in the amount of light, and a reduction in the size of the overall illuminating device can be achieved. Furthermore, by employing a concave curved mirror reflector consisting of a plurality of concave curved partial surfaces having different curvatures, the object being detected is present in an illuminated zone even if a fall trajectory of the object being detected deviates from an assumed fall trajectory, and therefore a shadow does not occur in a detection image obtained using a camera, and the image itself does not become dark. As a result,a deterioration in detection accuracy can be prevented.

The invention provides a target detection method and system based on a low-resolution image, and relates to the technical field of target detection. The method comprises the following steps: obtaining the low-resolution image of a to-be-detected target; performing feature extraction on the low-resolution image to obtain a corresponding feature map; processing the feature map to obtain a corresponding detection frame; processing the detection frame to obtain a coordinate and a classification probability score of the detection frame; and performing detection classification on the to-be-detected target according to the coordinate of the detection frame and the classification probability score. According to the method, the feature map with deep semantics can be extracted under the condition that the low-resolution image is not amplified, so that the detection time can be effectively shortened on the premise that the detection precision is not lost.

The present invention provides a method and system for target detection based on low-resolution images, which relate to the technical field of target detection, wherein the method includes the following steps: acquiring a low-resolution image of the target to be detected; performing feature analysis on the low-resolution image Extract the corresponding feature map; process the feature map to get the corresponding detection frame; process the detection frame to get the coordinates and classification probability score of the detection frame; detect and classify the target to be detected according to the coordinates of the detection frame and classification probability score. The present invention can extract feature maps with deep semantics without enlarging low-resolution images, thereby effectively reducing detection time without loss of detection accuracy.

The invention discloses a method and equipment for checking a liquid object by dual-energy computed tomography (CT). The method comprises the following steps of: performing data register (DR) scanning on the liquid object to acquire the transmission image of the checked liquid object; analyzing the pixel value of the transmission image to judge whether the transmission image is layered or not; performing dual-energy CT scanning on the checked liquid object at the at least one position of each determined layer to acquire dual-energy CT projection data; performing CT reconstruction according tothe projection data to acquire a CT image which indicates the physical attribute value of the checked liquid object; exacting the physical attribute value of the checked liquid object according to the CT image; and judging whether the checked liquid object is an dangerous object or not based on the physical attribute value. By the method, the liquid product can be quickly checked.

The invention discloses a method and equipment for simultaneously inspecting a plurality of liquid substances by using dual-energy computed tomography (CT). The method comprises the following steps of: performing dual-energy CT scanning on inspected liquid substances at a plurality of positions to acquire dual-energy CT protection data; rotating CT images of the inspected liquid substances after performing the dual-energy CT scanning at each position so as to align the images formed by multiple times of scanning operation; performing CT reconstruction according to the projection data to acquire the CT images for representing physical attribute values of the inspected liquid substances; extracting the physical attribute values of the inspected liquid substances according to the CT images; and judging whether the inspected liquid substances are suspicious based on the physical attribute values and reference physical attribute values of the liquid substances. By the method, the liquid substances can be inspected rapidly.

The present invention provides a face detection optimization method based on a deep convolutional cascaded network, which specifically includes the following steps: using the deep cascaded network to detect areas where human faces may appear, that is, hot spots; updating the hot spots, Set all the areas not in the hot zone to zero; perform data sparse compression on the obtained whole image. The invention greatly reduces the amount of redundant computation and improves the operating efficiency of the algorithm. The efficiency of the CNN network face detection algorithm on the front-end embedded platform can be increased by 20-30%, and the method of the present invention will not lose the detection accuracy, providing a better solution for the faster operation of the deep convolutional network on the front-end The scheme laid the foundation for the large-scale application of the network in the later stage.

The invention discloses a method and equipment for confirming a CT (Computed Tomography) scanning position in a dangerous goods inspection system. The method comprises the following steps of: firstly, through a CT scanning and dual-energy rebuilding method, obtaining one or more layers of CT images containing physical attributes of liquid to be tested; secondly, through an image processing and analyzing method, obtaining a physical attribute value of each liquid to be tested from the CT images; and finally, judging whether the liquid-state object to be tested is a dangerous goods or not according to the physical attribute value. The CT scanning method comprises a regular sectional CT scanning technology and a spiral CT scanning technology; and when the regular sectional CT scanning technology is utilized, a series of specific positions can be set so as to be scanned, a scanning position can be specified by an operator through a DR (Digital Radiography) image, and the position of a liquid part can be confirmed through automatic analysis on the DR image, so that CT scanning is guided.

The invention discloses a vehicle tracking method for an unmanned aerial vehicle based on an embedded platform, which mainly solves the problem in the prior art that the unmanned aerial vehicle loses tracking when vehicle tracking is blocked. The implementation steps are: 1. Train the vehicle classifier and mark the map; 2. Get a frame of image and initialize the tracking target; 3. Get a frame of image for target tracking; 4. Use the classifier to judge whether the target is blocked, if so, Go to step 5, otherwise go to step 8; 5. Determine whether the target is in the occluded area of ​​the map, if yes, go to step 6, otherwise go to step 7; 6. Perform target detection in the occluded area and make the drone hover, go to step 9; 7. Predict the target position; 8. Control the flight of the UAV according to the target; 9. Determine whether it is over, if so, end the tracking, otherwise return to step 3. The invention can detect and track the blocked target, improves the tracking robustness, and can be used for tracking vehicles on urban roads.